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

Focal and diffuse clinical subtypes in early-stage Parkinson’s disease: a one-year longitudinal study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Focal and diffuse clinical subtypes in early-stage Parkinson’s disease: a one-year longitudinal study Martin Johansson, Nina van Lier, Roy Kessels, Bastiaan Bloem, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1870271/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Feb, 2023 Read the published version in npj Parkinson's Disease → Version 1 posted 11 You are reading this latest preprint version Abstract 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 Figures Figure 1 Figure 2 Figure 3 Introduction 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 patients 7 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, PPP 8 ) 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 symptoms 7 . 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 PD 14 . 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 Netherlands 8 . 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. Results Subtyping Subtype classification was performed in accordance with the MMP-IM-DM criteria 7 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, η 2 h = 0.23]), bradykinesia [H(2) = 98.1 p < 0.001, η 2 h = 0.22], rigidity [H(2) = 44.2, p < 0.001, η 2 h = 0.096], PIGD [H(2) = 96.2, p < 0.001, η 2 h = 0.218], and self-reported motor symptoms (MDS-UPDRS-II total [H(2) = 117.9, p < 0.001, η 2 h = 0.266]). There were no between-subtype differences in the severity of resting or action tremor. See Fig. 1 A 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 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) I (p I (p II (p < 0.001) MDS-UPDRS-III total 26.63 (0.62) 30.21 (0.81) 44.62 (2.00) I (p I (p II (p < 0.001) Bradykinesia 12.55 (0.38) 14.92 (0.51) 23.31 (1.34) I (p I (p II (p < 0.001) Rigidity 4.85 (0.18) 5.32 (0.23) 7.55 (0.54) I (p = 0.005) III > I (p II (p < 0.001) PIGD 2.08 (0.10) 2.69 (0.11) 5.05 (0.20) I (p I (p 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) I (p I (p II (p < 0.001) Cognitive composite a 0.30 (0.04) -0.15 (0.59) -0.45 (0.75) II (p = 0.001) I > III (p III (p = 0.03) RBDSQ 2.1 (1.68) 4.75 (3.38) 5.92 (3.62) I (p I (p II (p = 0.012) SCOPA-AUT 12.79 (5.33) 19.14 (8.23) 22.94 (7.71) I (p I (p 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, η 2 h = 0.15]), poorer overall cognitive function (MoCA [H(2) = 16.1, p < 0.001, η 2 h = 0.032]) and more severe psychiatric problems, such as depression (BDI-II [H(2) = 73.1, p < 0.001, η 2 h = 0.16]), anxiety (STAI trait [F(2) = 34.1, p < 0.001, η 2 p = 0.14]; STAI state [F(2) = 25.8, p < 0.001, η 2 p = 0.11]), impulse control disorder (QUIP [H(2) = 32.5, p < 0.001, η 2 h = 0.07]), ophthalmologic problems (VIPD-Q [H(2) = 40.9, p < 0.001, η 2 h = 0.09]), in combination with reduced quality of life (PDQ-39 [F(2) = 68.2, p < 0.001, η 2 p = 0.24]). Furthermore, the diffuse-malignant subtype was characterized by older age [F(2) = 6.3, p = 0.002, η 2 p = 0.03], increased medication use (LEDD [H(2) = 9.4, p = 0.009, η 2 h = 0.019]), a higher proportion of men (sex [ꭓ 2 (2) = 10.8, p = 0.004]), and more severe stages of PD (Hoehn and Yahr-stage [ꭓ 2 (6) = 67.9, p < 0.001]). See Fig. 1 A 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) I (p I (p II (p < 0.001) MoCA 27.23 (0.15) 26.81 (0.17) 26.25 (0.27) II (p = 0.033) I > III (p III (p = 0.035 BDI-II 7.04 (0.39) 11.51 (0.45) 13.74 (0.75) I (p I (p < 0.001) STAI - Trait 31.91 (0.54) 38.07 (0.74) 40.76 (1.33) I (p I (p < 0.001) STAI - State 32.72 (0.52) 38.10 (0.70) 39.26 (1.19) I (p I (p < 0.001) QUIP 6.56 (0.68) 11.02 (0.78) 15 (1.31) I (p I (p < 0.001) PDQ-39 12.31 (0.48) 20.98 (0.92) 28.54 (2.14) I (p I (p II (p < 0.001) VIPD-Q 6.79 (0.51) 9.65 (0.59) 14.78 (1.01) I (p I (p 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) I (p II (p 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) II (p = 0.059) I > III (p III (p < 0.001) Arm vs. leg 0.28 (0.013) 0.26 (0.014) 0.16 (0.024) III (p 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, η 2 p = 0.02] and PIGD [H(2) = 19.8, p < 0.001, η 2 h = 0.04] and showed a trend towards less resting tremor [H(2) = 4.97, p = 0.083, η 2 h = 0.007]. See Fig. 1 B 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 arm 16 ). 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, η 2 h = 0.092] and arm-leg focality [H(2) = 21.3, p < 0.001, η 2 h = 0.045]). See Fig. 1 C 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, η 2 p = 0.018], ΔPIGD [F(2) = 4.1, p = 0.017, η 2 p = 0.023]), cognitive impairment (ΔMoCA [F(2) = 9.6, p < 0.001, η 2 p = 0.052]), trait anxiety (ΔSTAI trait [F(2) = 5.9, p = 0.003, η 2 p = 0.034]), impulse control disorder (ΔQUIP [F(2) = 6.6, p = 0.001, η 2 p = 0.044]), quality of life (ΔPDQ-39 F(2) = 3.4, p = 0.033, η 2 p = 0.02), and autonomic dysfunction (ΔSCOPA-AUT [F(2) = 4.5, p = 0.011, η 2 p = 0.028]). In addition, the diffuse-malignant subtype showed an increased proportion of PIGD (ΔPIGD proportion [F(2) = 4.4, p = 0.012, η 2 p = 0.026]). The diffuse-malignant subtype also showed trends toward faster progression of medication titration (ΔLEDD F(2) = 2.6, p = 0.077, η 2 p = 0.016), depression (ΔBDI-II [F(2) = 2.9, p = 0.054, η 2 p = 0.019]), and state anxiety (ΔSTAI state F(2) = 2.4, p = 0.09, η 2 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) II (p = 0.073) I > III (p 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 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, η 2 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, η 2 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 [χ 2 (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(χ 2 (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 . Discussion 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 PD 7 . 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 symptoms 17 . 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 tremor 16 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 criteria 12 . 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 processes 20 . 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 cortex 14 , disrupted functional connectivity patterns, reduced basal ganglia tissue integrity 21 , and more structural atrophy 7 . 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 system 25 , 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 PD 13 . 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 colleagues 7 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. Conclusion We applied a set of recently proposed clinical criteria 7 (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. Methods 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 years 8 . 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 PPP 8 . 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 Edition 39 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 function 7 . 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 above 15 . 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 MoCA 51 . 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 4 32 . 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 symptoms 22 . 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 progression 52 . 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 age 53 , sex 54 , and disease duration 30 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 interest 55 . 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. Declarations 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1870271","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":127105069,"identity":"7208194e-9ab6-4596-87f0-d74d43365b2c","order_by":0,"name":"Martin Johansson","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-9778-6278","institution":"Donders Institute for Brain, Cognition and Behaviour","correspondingAuthor":true,"prefix":"","firstName":"Martin","middleName":"","lastName":"Johansson","suffix":""},{"id":127105070,"identity":"a54e283e-3ad1-4c65-b653-8978f4dd0c69","order_by":1,"name":"Nina van Lier","email":"","orcid":"","institution":"Donders Institute for Brain, Cognition and Behaviour","correspondingAuthor":false,"prefix":"","firstName":"Nina","middleName":"van","lastName":"Lier","suffix":""},{"id":127105071,"identity":"b9a86010-406d-4170-95cb-ace14e4a3334","order_by":2,"name":"Roy Kessels","email":"","orcid":"https://orcid.org/0000-0001-9500-9793","institution":"Donders Institute for Brain, Cognition and Behaviour","correspondingAuthor":false,"prefix":"","firstName":"Roy","middleName":"","lastName":"Kessels","suffix":""},{"id":127105072,"identity":"b895751e-7ae5-4cbb-9b32-15c2f50265a0","order_by":3,"name":"Bastiaan Bloem","email":"","orcid":"","institution":"Radboud University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Bastiaan","middleName":"","lastName":"Bloem","suffix":""},{"id":127105073,"identity":"712d00a5-2851-456d-bbd5-2d67a58f067c","order_by":4,"name":"Rick Helmich","email":"","orcid":"","institution":"Radboud University Nijmegen Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Rick","middleName":"","lastName":"Helmich","suffix":""}],"badges":[],"createdAt":"2022-07-18 13:53:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1870271/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1870271/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41531-023-00466-4","type":"published","date":"2023-02-17T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":25001990,"identity":"0293b65a-0cc5-4d97-aece-d130590f6e2c","added_by":"auto","created_at":"2022-08-09 18:07:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":257914,"visible":true,"origin":"","legend":"\u003cp\u003eBaseline characteristics. A) Estimated marginal means of baseline severity derived from linear models adjusting for age, sex, and disease duration. Each separate row has been scaled and demeaned to visualize the direction of differences. Greyed-out rows reflect non-significant effects of SUBTYPE, as assessed using one-way ANCOVAs, on specific measurements. B) Motor symptom subscores represented as percentages of the total MDS-UPDRS-III score. Error bars indicate 95% confidence intervals around the mean. C) Severity of motor symptoms for the right side relative to the left side (upper) and for arm relative to leg (lower). Higher lateralization and focality indices entail that motor symptoms are more severe on one side or for one specific part of the body, respectively. MMP=Mild-motor predominant, IM=Intermediate, DM=Diffuse-malignant + p\u0026lt;0.1, * p\u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"OnlineFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1870271/v1/e601f80947f0f4e5a8de0f1f.png"},{"id":25001427,"identity":"b2934c49-7720-4ecc-a46a-632248e129c9","added_by":"auto","created_at":"2022-08-09 18:02:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":212375,"visible":true,"origin":"","legend":"\u003cp\u003eOne-year progression. Estimated marginal means of one-year progression derived from linear models adjusted for age, sex, disease duration, and baseline severity. Each separate row of the heatmap (left) has been scaled and demeaned to visualize the direction of differences. Greyed-out rows reflect non-significant effects of SUBTYPE, as assessed using one-way ANCOVAs, on specific measurements. Each measure showing a significant effect of subtype is visualized individually (right). MMP=Mild-motor predominant, IM=Intermediate, DM=Diffuse-malignant, * p\u0026lt;0.05, ** p\u0026lt;0.01, *** p\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1870271/v1/73a481c98561406f18f0cd99.png"},{"id":25001428,"identity":"9c4b3555-efa4-4194-a124-1999bb58c844","added_by":"auto","created_at":"2022-08-09 18:02:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":79024,"visible":true,"origin":"","legend":"\u003cp\u003eConversions in subtype classification from baseline to one-year follow-up. A) Counts following classification using z-scores derived from baseline data only. B) Counts following classification using z-scores derived from each specific session. k=Cohen’s kappa, MMP=Mild-motor predominant, IM=Intermediate, DM=Diffuse-malignant.\u003c/p\u003e","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1870271/v1/0d38ebb703d966d6dcae488f.png"},{"id":33116834,"identity":"d149ddef-36c8-484e-8f2d-57e536621d6c","added_by":"auto","created_at":"2023-02-18 08:09:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1384563,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1870271/v1/e2baa17a-ee58-4861-ac30-6768815a00f3.pdf"}],"financialInterests":"(Not answered)","formattedTitle":"Focal and diffuse clinical subtypes in early-stage Parkinson’s disease: a one-year longitudinal study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParkinson\u0026rsquo;s disease (PD) is a neurodegenerative disorder that is characterized by marked between-patient variability in clinical phenotype and prognosis\u003csup\u003e1,2\u003c/sup\u003e. 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\u003csup\u003e3,4\u003c/sup\u003e. 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\u003csup\u003e5,6\u003c/sup\u003e. In this study, we aimed to validate a set of clinical criteria that has recently been proposed for the subtyping of de novo PD patients\u003csup\u003e7\u003c/sup\u003e 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, PPP\u003csup\u003e8\u003c/sup\u003e) to investigate subtype-specific differences in clinical baseline characteristics and disease progression.\u003c/p\u003e \u003cp\u003eTraditional 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)\u003csup\u003e9\u0026ndash;11\u003c/sup\u003e 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 symptoms\u003csup\u003e7\u003c/sup\u003e. 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 \u0026ndash; 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.\u003c/p\u003e \u003cp\u003eTwo 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\u003csup\u003e12,13\u003c/sup\u003e. 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 PD\u003csup\u003e14\u003c/sup\u003e. However, further validation and independent replication of these criteria is necessary to establish their usability in additional stages of PD.\u003c/p\u003e \u003cp\u003eIn 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\u0026ndash;5 years disease duration) who participated in the Personalized Parkinson Project (PPP) in the Netherlands\u003csup\u003e8\u003c/sup\u003e. 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\u0026ndash;45; 46\u0026ndash;55; 56\u0026ndash;65; \u0026ge;66 years), and different disease durations (\u0026lt;\u0026thinsp;2.5 years; \u0026ge;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.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubtyping\u003c/h2\u003e \u003cp\u003eSubtype classification was performed in accordance with the MMP-IM-DM criteria\u003csup\u003e7\u003c/sup\u003e after splitting the cohort patients at the median disease duration (33 months)\u003csup\u003e15\u003c/sup\u003e. 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\u0026thinsp;=\u0026thinsp;214, 48%), intermediate (n\u0026thinsp;=\u0026thinsp;167, 38%), and diffuse-malignant (n\u0026thinsp;=\u0026thinsp;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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eBetween-subtype differences in baseline characteristics\u003c/h2\u003e \u003cp\u003e \u003cb\u003eClinical measurements used to implement the MMP-IM-DM criteria.\u003c/b\u003e 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.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). 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)\u0026thinsp;=\u0026thinsp;103, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.23]), bradykinesia [H(2)\u0026thinsp;=\u0026thinsp;98.1 p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.22], rigidity [H(2)\u0026thinsp;=\u0026thinsp;44.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.096], PIGD [H(2)\u0026thinsp;=\u0026thinsp;96.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.218], and self-reported motor symptoms (MDS-UPDRS-II total [H(2)\u0026thinsp;=\u0026thinsp;117.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.266]). There were no between-subtype differences in the severity of resting or action tremor. See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic information and clinical characteristics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild-motor predominant (I)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate (II)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiffuse-malignant (III)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePost-hoc\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCount (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.69 (9.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.22 (8.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.42 (7.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.039)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (F/M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104/110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62/105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17/45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease duration (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.44 (16.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.94 (18.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.45 (17.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.43 (4.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.11 (4.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.58 (4.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoehn \u0026amp; Yahr-stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27/174/13/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13/140/13/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0/37/21/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLEDD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e470.28 (253.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e591.39 (366.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e612.83 (335.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.029)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.007)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical scores used for subtype classification\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMotor composite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.30 (4.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.69 (5.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.77 (4.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS-UPDRS-III total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.63 (0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.21 (0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.62 (2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBradykinesia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.55 (0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.92 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.31 (1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRigidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.85 (0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.32 (0.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.55 (0.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.005)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.08 (0.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.69 (0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.05 (0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResting tremor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.21 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.25 (0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4 (0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAction tremor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.11 (0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.19 (0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.75 (0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS-UPDRS-II total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.71 (0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.66 (0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.65 (0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive composite \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30 (0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.15 (0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.45 (0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;=\u0026thinsp;0.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBDSQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1 (1.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.75 (3.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.92 (3.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.012)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCOPA-AUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.79 (5.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.14 (8.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.94 (7.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.016)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote.\u003c/b\u003e Estimated marginal means (standard errors) adjusting for age, sex, and disease duration where appropriate. \u003csup\u003ea\u003c/sup\u003e z-score based on age-, education,- and/or sex-adjusted normative comparison; MDS-UPDRS\u0026thinsp;=\u0026thinsp;Movement Disorders Society Unified Parkinson Disease Rating Scale; F\u0026thinsp;=\u0026thinsp;Female; LEDD\u0026thinsp;=\u0026thinsp;Levodopa equivalent daily dose; M\u0026thinsp;=\u0026thinsp;Male; N\u0026thinsp;=\u0026thinsp;Number of participants; RBDSQ\u0026thinsp;=\u0026thinsp;REM sleep behavior disorder screening questionnaire; SCOPA-AUT\u0026thinsp;=\u0026thinsp;Scales for Outcomes in Parkinson\u0026rsquo;s Disease, autonomic section.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical measurements withheld during subtype classification.\u003c/b\u003e 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)\u0026thinsp;=\u0026thinsp;66.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.15]), poorer overall cognitive function (MoCA [H(2)\u0026thinsp;=\u0026thinsp;16.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.032]) and more severe psychiatric problems, such as depression (BDI-II [H(2)\u0026thinsp;=\u0026thinsp;73.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.16]), anxiety (STAI trait [F(2)\u0026thinsp;=\u0026thinsp;34.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.14]; STAI state [F(2)\u0026thinsp;=\u0026thinsp;25.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.11]), impulse control disorder (QUIP [H(2)\u0026thinsp;=\u0026thinsp;32.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.07]), ophthalmologic problems (VIPD-Q [H(2)\u0026thinsp;=\u0026thinsp;40.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.09]), in combination with reduced quality of life (PDQ-39 [F(2)\u0026thinsp;=\u0026thinsp;68.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.24]). Furthermore, the diffuse-malignant subtype was characterized by older age [F(2)\u0026thinsp;=\u0026thinsp;6.3, p\u0026thinsp;=\u0026thinsp;0.002, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.03], increased medication use (LEDD [H(2)\u0026thinsp;=\u0026thinsp;9.4, p\u0026thinsp;=\u0026thinsp;0.009, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.019]), a higher proportion of men (sex [ꭓ\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;10.8, p\u0026thinsp;=\u0026thinsp;0.004]), and more severe stages of PD (Hoehn and Yahr-stage [ꭓ\u003csup\u003e2\u003c/sup\u003e(6)\u0026thinsp;=\u0026thinsp;67.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001]). See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel-based predictions of clinical measurements at baseline.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild-motor predominant (I)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate (II)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiffuse-malignant (III)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePost-hoc\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical scores withheld from subtype classification\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.63 (0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.36 (0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.30 (0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.23 (0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.81 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.25 (0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.033)\u003c/p\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;=\u0026thinsp;0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBDI-II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.04 (0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.51 (0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.74 (0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTAI - Trait\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.91 (0.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.07 (0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.76 (1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTAI - State\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.72 (0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.10 (0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.26 (1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQUIP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.56 (0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.02 (0.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePDQ-39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.31 (0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.98 (0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.54 (2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVIPD-Q\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.79 (0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.65 (0.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.78 (1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMotor symptom subscores relative to total MDS-UPDRS-III\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBradykinesia (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.25 (0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26 (0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28 (0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRigidity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23 (0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.23 (0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22 (0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIGD (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.12 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17 (0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResting tremor (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10 (0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09 (0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07 (0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;=\u0026thinsp;0.085)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAction tremor (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10 (0.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10 (0.010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.14 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14 (0.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLocalization of bradykinesia-rigidity symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight vs. left\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28 (0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26 (0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16 (0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.059)\u003c/p\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArm vs. leg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.28 (0.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26 (0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16 (0.024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003eNote.\u003c/b\u003e Estimated marginal means (standard errors) of baseline score adjusting for age, sex, and disease duration. PIGD\u0026thinsp;=\u0026thinsp;Postural instability and gait disturbance; ROMP\u0026thinsp;=\u0026thinsp;Radboud Oral Inventory for Parkinson\u0026rsquo;s Disease; MoCA\u0026thinsp;=\u0026thinsp;Montreal Cognitive Assessment; BDI\u0026thinsp;=\u0026thinsp;Beck\u0026rsquo;s Depression Index; STAI\u0026thinsp;=\u0026thinsp;State-Trait Anxiety Inventory; QUIP\u0026thinsp;=\u0026thinsp;Questionnaire for Impulsive-Compulsive Disorders in Parkinson\u0026rsquo;s Disease; PDQ\u0026thinsp;=\u0026thinsp;Parkinson\u0026rsquo;s Disease Questionnaire; VIPD-Q\u0026thinsp;=\u0026thinsp;Visual Impairment in Parkinson\u0026rsquo;s Disease Questionnaire.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePartitioning of overall motor symptom severity.\u003c/b\u003e 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)\u0026thinsp;=\u0026thinsp;3.5, p\u0026thinsp;=\u0026thinsp;0.031, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.02] and PIGD [H(2)\u0026thinsp;=\u0026thinsp;19.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.04] and showed a trend towards less resting tremor [H(2)\u0026thinsp;=\u0026thinsp;4.97, p\u0026thinsp;=\u0026thinsp;0.083, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.007]. See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. 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 \u0026ge;\u0026thinsp;2 for at least one arm\u003csup\u003e16\u003c/sup\u003e). 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.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLocalization of bradykinesia-rigidity symptoms.\u003c/b\u003e 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)\u0026thinsp;=\u0026thinsp;41.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.092] and arm-leg focality [H(2)\u0026thinsp;=\u0026thinsp;21.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eh\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.045]). See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBetween-subtype differences in one-year clinical progression\u003c/h2\u003e \u003cp\u003eComparisons 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)\u0026thinsp;=\u0026thinsp;3.14, p\u0026thinsp;=\u0026thinsp;0.043, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.018], ΔPIGD [F(2)\u0026thinsp;=\u0026thinsp;4.1, p\u0026thinsp;=\u0026thinsp;0.017, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.023]), cognitive impairment (ΔMoCA [F(2)\u0026thinsp;=\u0026thinsp;9.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.052]), trait anxiety (ΔSTAI trait [F(2)\u0026thinsp;=\u0026thinsp;5.9, p\u0026thinsp;=\u0026thinsp;0.003, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.034]), impulse control disorder (ΔQUIP [F(2)\u0026thinsp;=\u0026thinsp;6.6, p\u0026thinsp;=\u0026thinsp;0.001, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.044]), quality of life (ΔPDQ-39 F(2)\u0026thinsp;=\u0026thinsp;3.4, p\u0026thinsp;=\u0026thinsp;0.033, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.02), and autonomic dysfunction (ΔSCOPA-AUT [F(2)\u0026thinsp;=\u0026thinsp;4.5, p\u0026thinsp;=\u0026thinsp;0.011, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.028]). In addition, the diffuse-malignant subtype showed an increased proportion of PIGD (ΔPIGD proportion [F(2)\u0026thinsp;=\u0026thinsp;4.4, p\u0026thinsp;=\u0026thinsp;0.012, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.026]). The diffuse-malignant subtype also showed trends toward faster progression of medication titration (ΔLEDD F(2)\u0026thinsp;=\u0026thinsp;2.6, p\u0026thinsp;=\u0026thinsp;0.077, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.016), depression (ΔBDI-II [F(2)\u0026thinsp;=\u0026thinsp;2.9, p\u0026thinsp;=\u0026thinsp;0.054, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.019]), and state anxiety (ΔSTAI state F(2)\u0026thinsp;=\u0026thinsp;2.4, p\u0026thinsp;=\u0026thinsp;0.09, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.015). See Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel-based predictions of 1-year progression on clinical measurements.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild-motor predominant (I)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate (II)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiffuse-malignant (III)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePost-hoc\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e% imputed data\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMotor symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔLEDD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.67 (15.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132.09 (16.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102.91 (30.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔMotor composite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.82 (0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11 (0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.83 (0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔMDS-UPDRS-III total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.15 (0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.73 (0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3 (1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔBradykinesia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.70 (0.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14 (0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.12 (0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.031)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.082)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔRigidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.62 (0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68 (0.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 (0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔPIGD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.29 (0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10 (0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.36 (0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.035)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (P\u0026thinsp;=\u0026thinsp;0.059)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔResting tremor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.38 (0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18 (0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔAction tremor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.04 (0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.03 (0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29 (0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔMDS-UPDRS-II total\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.08 (0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51 (0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.73 (0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔROMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.18 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004 (0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22 (0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMotor symptom subscores relative to total MDS-UPDRS-III\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔBradykinesia (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔRigidity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔPIGD (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.02 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.01 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔResting tremor (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔAction tremor (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.01 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.01 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔOther (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01 (0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiffusivity of bradykinesia-rigidity symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔRight vs. left\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.03 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.03 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.04 (0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔArm vs. leg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.02 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.02 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;0.01 (0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-motor symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔMoCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.28 (0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.79 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.72 (0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.073)\u003c/p\u003e \u003cp\u003eI\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;III (p\u0026thinsp;=\u0026thinsp;0.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔBDI-II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.59 (0.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.08 (0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.03 (0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSTAI - Trait\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.44 (0.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43 (0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.45 (0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.017)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSTAI - State\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.33 (0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.65 (0.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 (0.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.075)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔQUIP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.35 (0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.85 (0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.30 (1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔPDQ-39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.70 (0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.33 (0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5 (1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔRBDSQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00 (0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32 (0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04 (0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔSCOPA-AUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.14 (0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.46 (0.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.47 (0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;I (p\u0026thinsp;=\u0026thinsp;0.008)\u003c/p\u003e \u003cp\u003eIII\u0026thinsp;\u0026gt;\u0026thinsp;II (p\u0026thinsp;=\u0026thinsp;0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eΔVIPD-Q\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.21 (0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.73 (0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.55 (0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNote.\u003c/b\u003e Estimated marginal means (standard errors) of 1-year progression adjusting for age, sex, disease duration and baseline score. Δ\u0026thinsp;=\u0026thinsp;Delta (follow-up \u0026ndash; baseline).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analyses\u003c/h2\u003e \u003cp\u003e \u003cb\u003eAnalyses on imputed versus non-imputed data sets.\u003c/b\u003e 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)\u0026thinsp;=\u0026thinsp;3.1, p\u0026thinsp;=\u0026thinsp;0.048, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.02]).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAnalyses on subtype classifications based on cognitive composite scores versus binary MCI.\u003c/b\u003e 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\u0026thinsp;=\u0026thinsp;0.31). Agreement between these two classifications was substantial (k\u0026thinsp;=\u0026thinsp;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)\u0026thinsp;=\u0026thinsp;3.4, p\u0026thinsp;=\u0026thinsp;0.036, η\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.02).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSubtype conversions\u003c/h2\u003e \u003cp\u003e \u003cb\u003eSubtype conversions relative to baseline cohort-level scores.\u003c/b\u003e 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\u0026thinsp;=\u0026thinsp;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 [χ\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;5.51, p\u0026thinsp;=\u0026thinsp;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.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSubtype conversions relative to session-specific cohort-level scores.\u003c/b\u003e 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\u0026thinsp;=\u0026thinsp;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(χ\u003csup\u003e2\u003c/sup\u003e(2)\u0026thinsp;=\u0026thinsp;4.82, p\u0026thinsp;=\u0026thinsp;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.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe employed the clinical subtyping strategy of Fereshtehnejad and colleagues (the MMP-IM-DM criteria)\u003csup\u003e7\u003c/sup\u003e 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\u003csup\u003e7,12,13\u003c/sup\u003e, thereby validating the use of the MMP-IM-DM criteria, but now for early-stage PD.\u003c/p\u003e \u003cp\u003eApplication 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 PD\u003csup\u003e7\u003c/sup\u003e. 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\u003csup\u003e7,12,13\u003c/sup\u003e. 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.\u003c/p\u003e \u003cp\u003eTraditional subtyping approaches in PD research often classify patients based on the presence or absence of tremor and PIGD symptoms\u003csup\u003e17\u003c/sup\u003e. 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\u003csup\u003e17\u0026ndash;19\u003c/sup\u003e. 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 tremor\u003csup\u003e16\u003c/sup\u003e 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 criteria\u003csup\u003e12\u003c/sup\u003e. 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.\u003c/p\u003e \u003cp\u003eClinical differences between PD subtypes may be partially explained by heterogeneity in neural mechanisms and pathological processes\u003csup\u003e20\u003c/sup\u003e. 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 cortex\u003csup\u003e14\u003c/sup\u003e, disrupted functional connectivity patterns, reduced basal ganglia tissue integrity\u003csup\u003e21\u003c/sup\u003e, and more structural atrophy\u003csup\u003e7\u003c/sup\u003e. These findings support the hypothesis that subtypes may differ with respect to underlying pathological processes, such as the accumulation and spread of ɑ-synuclein\u003csup\u003e20,22\u0026minus;24\u003c/sup\u003e. Recent evidence suggests that PD-related ɑ-synucleinopathy may spread bi-directionally between the central and peripheral nervous system\u003csup\u003e25\u003c/sup\u003e, and that the specific direction of this spread may be associated with different clinical phenotypes of PD\u003csup\u003e20,22,23\u003c/sup\u003e. 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\u003csup\u003e22,24\u003c/sup\u003e. 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.\u003c/p\u003e \u003cp\u003ePrevious research has shown that subtypes may not be stable over time\u003csup\u003e12,26\u0026minus;30\u003c/sup\u003e. Subtype conversions could result from disease progression such that all patients converge towards a diffuse-malignant phenotype in late-stage PD\u003csup\u003e13\u003c/sup\u003e. 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%)\u003csup\u003e26\u003c/sup\u003e. 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.\u003c/p\u003e \u003cp\u003eThe subtyping approach proposed by Fereshtehnejad and colleagues\u003csup\u003e7\u003c/sup\u003e 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.\u003c/p\u003e \u003cp\u003eOur study included patients with a range of disease durations from 0 to 5 years, which may have influenced subtype classifications\u003csup\u003e15,30\u003c/sup\u003e. 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\u003csup\u003e7,12,13\u003c/sup\u003e, indicating that the median split did not bias subtype classification in favor of any one subtype.\u003c/p\u003e \u003cp\u003eTwo 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.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe applied a set of recently proposed clinical criteria\u003csup\u003e7\u003c/sup\u003e (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\u003csup\u003e7,12,13\u003c/sup\u003e, 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.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eBaseline 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 years\u003csup\u003e8\u003c/sup\u003e. 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\u0026ndash;2934). Patients were eligible for the study if they were diagnosed with idiopathic PD by a certified neurologist, had 0\u0026ndash;5 years disease duration, were \u0026ge;\u0026thinsp;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\u0026thinsp;=\u0026thinsp;8) or other (n\u0026thinsp;=\u0026thinsp;3). These participants were excluded from further analyses. Further details can be found in the primary study protocol of the PPP\u003csup\u003e8\u003c/sup\u003e. Demographic information can be found in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eClinical measurements\u003c/h2\u003e \u003cp\u003eMotor symptoms were assessed in an off-medicated state (\u0026gt;\u0026thinsp;12h withdrawal) with the Movement Disorders Society Unified Parkinson Disease Rating Scale (MDS-UPDRS)\u003csup\u003e31\u003c/sup\u003e part III by a trained assessor. Subscores of the MDS-UPDRS-III were defined for bradykinesia (11 scores, items 4\u0026ndash;9 and 14), rigidity (5 scores, item 3), resting tremor (5 scores, items 17\u0026ndash;18, jaw/lip tremor score excluded), action tremor (4 scores, items 15\u0026ndash;16), and postural instability and gait disturbance (PIGD; 5 scores, MDS-UPDRS-III items 10\u0026ndash;12 and MDS-UPDRS-II items 12\u0026ndash;13)\u003csup\u003e9,32\u003c/sup\u003e. 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\u0026rsquo;s Disease (ROMP)\u003csup\u003e33\u003c/sup\u003e. Cognitive performance was assessed with the Montreal Cognitive Assessment (MoCA)\u003csup\u003e34\u003c/sup\u003e as a measure of overall cognition, the Benton Judgement of Line Orientation (Benton JLO)\u003csup\u003e35\u003c/sup\u003e as a test of visuospatial perception, the Brixton Spatial Anticipation Test (Brixton)\u003csup\u003e36\u003c/sup\u003e that assesses executive function, the Semantic Fluency Test (SFT; 1-minute animal naming)\u003csup\u003e37\u003c/sup\u003e as a measure of verbal fluency, the Symbol Digit Modalities Test (SDMT, 90 seconds, oral version)\u003csup\u003e38\u003c/sup\u003e measuring processing speed, Letter-Number Sequencing (LNS) from the Wechsler Adult Intelligence Test \u0026ndash; Fourth Edition\u003csup\u003e39\u003c/sup\u003e as an index of working memory, and the Rey Auditory Verbal Learning Test (RAVLT)\u003csup\u003e37,40\u003c/sup\u003e as a test of episodic memory. Autonomic function was assessed with the Scales for Outcomes in Parkinson\u0026rsquo;s disease (SCOPA-AUT)\u003csup\u003e41\u003c/sup\u003e. REM-sleep behavior was assessed with the REM Sleep Behavior Disorder Screening Questionnaire (RBDSQ)\u003csup\u003e42\u003c/sup\u003e. Neuropsychiatric symptoms were assessed with the Beck Depression Inventory (BDI-II)\u003csup\u003e43\u003c/sup\u003e, State-Trait Anxiety Inventory (STAI)\u003csup\u003e44\u003c/sup\u003e, and Questionnaire for Impulsive-Compulsive Disorders in PD (QUIP)\u003csup\u003e45\u003c/sup\u003e. Quality of life was assessed with the Parkinson\u0026rsquo;s Disease Questionnaire-39 (PDQ-39)\u003csup\u003e46,47\u003c/sup\u003e. Ophthalmologic problems were assessed with the Visual Impairment in Parkinson\u0026rsquo;s Disease Questionnaire (VIPD-Q)\u003csup\u003e48\u003c/sup\u003e. Progression was defined for each clinical measurement as between-session difference scores (deltas; follow-up \u0026ndash; baseline).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSubtype classification\u003c/h2\u003e \u003cp\u003eImplementation of the MMP-IM-DM criteria depends on assessments of four clinical domains: motor symptoms, cognitive function, REM-sleep behavior disorder, and autonomic function\u003csup\u003e7\u003c/sup\u003e. 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\u0026ndash;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\u003csup\u003e49,50\u003c/sup\u003e. 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 \u0026ndash; 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 above\u003csup\u003e15\u003c/sup\u003e. 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.\u003c/p\u003e \u003cp\u003eClassification 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).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSubtype conversions\u003c/h2\u003e \u003cp\u003eSubtype 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 MoCA\u003csup\u003e51\u003c/sup\u003e. 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePartitioning of overall motor symptom severity\u003c/h2\u003e \u003cp\u003eProportions 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 4\u003csup\u003e32\u003c/sup\u003e. Each subscore was divided by the sum of all scaled subscores to express each subscore as a percentage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLocalization of bradykinesia-rigidity symptoms\u003c/h2\u003e \u003cp\u003eMotor 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 symptoms\u003csup\u003e22\u003c/sup\u003e. 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\u0026thinsp;=\u0026thinsp;151 [38%]; action tremor, n\u0026thinsp;=\u0026thinsp;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\u0026thinsp;+\u0026thinsp;left). Arm-leg focality was calculated in the same way (|arm - leg|/arm\u0026thinsp;+\u0026thinsp;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).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e \u003cb\u003eData preparation and imputation of missing data.\u003c/b\u003e All data preparation and statistical analysis were conducted in R (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.com\u003c/span\u003e\u003cspan address=\"https://www.r-project.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). 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 progression\u003csup\u003e52\u003c/sup\u003e. For analyses of progression, the number of imputed data sets were calculated as the percentage of missing data (see Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) times 5. Each imputation was iterated 10 times.\u003c/p\u003e \u003cp\u003e \u003cb\u003eBetween-subtype comparisons of clinical phenotype and progression.\u003c/b\u003e 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 age\u003csup\u003e53\u003c/sup\u003e, sex\u003csup\u003e54\u003c/sup\u003e, and disease duration\u003csup\u003e30\u003c/sup\u003e 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 interest\u003csup\u003e55\u003c/sup\u003e. 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\u0026rsquo;s kappa.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: The Michael J. Fox Foundation for Parkinson\u0026rsquo;s Research. The Center of Expertise for Parkinson \u0026amp; Movement Disorders was supported by a center of excellence grant of the Parkinson\u0026rsquo;s Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the patients who participated in the Personalized Parkinson Project, the assessors who performed data collection during this project, and the technical team from \u0026lsquo;Polymorphic encryption and pseudonymization for personalized healthcare\u0026rsquo; 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).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNML, 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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNothing to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrespondence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests for materials should be addressed to Martin E. Johansson.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical dataset analyzed during the current study will be made publicly available upon the completion of the Personalized Parkinson Project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analyses in the current study were conducted using publicly available \u0026lsquo;R\u0026rsquo;-packages. Rmarkdown files containing the analysis code can be made available upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLewis, S. J. G. \u003cem\u003eet al.\u003c/em\u003e Heterogeneity of Parkinson\u0026rsquo;s disease in the early clinical stages using a data driven approach. \u003cem\u003eJ. Neurol. Neurosurg. 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Pooling ANOVA Results From Multiply Imputed Datasets. \u003cem\u003eMethodology\u003c/em\u003e \u003cb\u003e12\u003c/b\u003e, 75\u0026ndash;88 (2016).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-parkinsons-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjparkd","sideBox":"Learn more about [npj Parkinson's Disease](http://www.nature.com/npjparkd/)","snPcode":"41531","submissionUrl":"https://submission.springernature.com/new-submission/41531/3","title":"npj Parkinson's Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Parkinson’s disease, subtype, clinical progression, longitudinal","lastPublishedDoi":"10.21203/rs.3.rs-1870271/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1870271/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHeterogeneity 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.\u003c/p\u003e","manuscriptTitle":"Focal and diffuse clinical subtypes in early-stage Parkinson’s disease: a one-year longitudinal study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-09 18:02:53","doi":"10.21203/rs.3.rs-1870271/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2022-09-02T09:16:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-08-29T03:49:55+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-08-21T00:47:24+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2022-08-10T14:48:40+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-08-08T15:17:48+00:00","index":3,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-08-08T00:04:24+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2022-08-07T22:52:38+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2022-08-07T20:49:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-07-20T05:39:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-07-18T13:49:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Parkinson's Disease","date":"2022-07-18T13:49:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-parkinsons-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjparkd","sideBox":"Learn more about [npj Parkinson's Disease](http://www.nature.com/npjparkd/)","snPcode":"41531","submissionUrl":"https://submission.springernature.com/new-submission/41531/3","title":"npj Parkinson's Disease","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"13622c44-e7cc-4133-bac2-df5ec7dbc0aa","owner":[],"postedDate":"August 9th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-02-18T08:09:01+00:00","versionOfRecord":{"articleIdentity":"rs-1870271","link":"https://doi.org/10.1038/s41531-023-00466-4","journal":{"identity":"npj-parkinsons-disease","isVorOnly":false,"title":"npj Parkinson's Disease"},"publishedOn":"2023-02-17 05:00:00","publishedOnDateReadable":"February 17th, 2023"},"versionCreatedAt":"2022-08-09 18:02:53","video":"","vorDoi":"10.1038/s41531-023-00466-4","vorDoiUrl":"https://doi.org/10.1038/s41531-023-00466-4","workflowStages":[]},"version":"v1","identity":"rs-1870271","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1870271","identity":"rs-1870271","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}