Study Participants

Appendix e-1

METHODS

Study Participants

Patients were included if they were diagnosed by a movement disorders specialist as having idiopathic Parkinson's disease (PD) (as defined by the UK Brain Bank criteria), if they were between 40 and 85 years of age, and if they were not demented

(i.e., Mini Mental State Examination (MMSE) score > 24) e1. Patients were excluded if they had brain surgery in the past, including implanted deep brain stimulation, or if they had significant co-morbidities likely to affect gait, e.g., acute illness, orthopedic disease, or history of stroke. A total of 110 patients with idiopathic PD were recruited for this study.

Clinical evaluation

Patients were assessed using the motor part (III) of the Unified Parkinson’s Disease

Rating Scale (UPDRS) e2. The pull test (item 30) was used as a marker of balance and postural control and other items were used to classify the patients into two motor subtypes, as detailed in the text. This assessment was conducted in the "OFF" state after at least 12 hours of overnight withdrawal of anti-parkinsonian medications.

Balance and postural control were also evaluated using the Berg Balance Scale

(BBS)e3. Gait speed (m/sec) was determined by measuring the average time the subject walked the middle 10 meters of the corridor under single and dual task conditions (i.e., serial 3 subtracting). A computerized cognitive battery (Mindstreams,

NeuroTrax, Corp., Texas)e4 was used in the "ON" state to sample a wide range of

1 cognitive domains and to generate an executive function (EF) index and a global cognitive score (GCS). The battery was previously validated in patients with PD e5-e7.

In addition, symptoms were quantified using PIGD and TD scores that reflect gait and balance difficulties and tremor severity, respectively e8. The PIGD score and tremor score were based on the sum score of items from part II (interview) and part III (PD related motor symptoms) of the UPDRS, as originally described by Jankovic et al. e8.

The PIGD score summed 5 items contributing to postural instability and gait difficulties (e.g., pull test, walking and freezing of gait). The tremor score summed 9 items contributing to rest, postural and action tremor. Classification into PIGD and

TD subtypes was based on these scores as detailed in the text.

Since cerebro-vascular risk factors have been associated with WM changes e9 , cerebro-vascular risk factors were also assessed by history (i.e., high blood pressure, diabetes, hypercholesterolemia, years of smoking). Further, the total number of risk factors was computed as a cerebro-vascular risk index (table e-1).

MRI acquisition

A high-resolution T1-weighted brain volume (BRAVO) acquisition was used with the following parameters to ascertain GM changes: Repetition Time (TR) = 9000 milliseconds, TE = 3.6 milliseconds, flip angle = 90, voxel size = 1×1x1, matrix =

256x256, FOV = 250X250 mm2.

The resting-state fMRI scans were performed using an echo planar imaging (EPI) sequence with the following scan parameters: Repetition Time (TR) = 1,680 milliseconds, TE = 35 milliseconds, flip angle = 90, slice thickness = 3.5 mm, matrix

= 64x64, FOV = 200x200 mm2.

2 Voxel-based morphometry data analysis

Analysis of whole brain GM volumes was performed as implemented in the VBM toolbox (http://dbm.neuro.uni-jena.de/vbm.html) in SPM5 (Wellcome Department of

Imaging Neuroscience Group, London, UK; http://www.fil.ion.ucl.ac.uk/spm/).

Preprocessing was completed using the VBM default settings for a non-linearly modulated normalized VBM (i.e., total brain volume served as a covariate). First, a customized GM (GM) template was generated and subsequently used to normalize all of the structural images in native space into the stereotaxic Montreal Neurological

Institute (MNI) space. Then, T1-weighted structural images were re-sliced to

1.5 mm × 1.5 mm × 1.5 mm, and then segmented into GM, white matter and cerebrospinal fluid. Spatial smoothing of the normalized GM images was conducted by application of an 8 mm full-width at half-maximum (FWHM) Gaussian kernel.

The percentage of GM voxels was calculated by counting the number of voxels with intensity of 80% or more of the average GM template as defined in SPM5.

Whole brain comparison of GM volume was performed using analysis of variance

(ANOVA) as implemented in SPM5. The model was adjusted for age and disease duration.

Resting-state functional connectivity analysis In order to define the motor network, the more affected putamen was selected as the seed region for each patient. The putamen was selected as it is one of the main regions affected by dopamine depletion in PD e10, and it has an important role in motor control e11. Resting state fMRI data were first pre-processed using Statistical Parametric

Mapping (SPM5) software. All images were realigned to the first one to correct for

3 subject motion. Head movements were calculated for each subject using the realignment parameters estimated by SPM5. No difference were found in head movement between the groups (mean cumulative translations: 0.34 mm, SD = 0.14, and 0.39 mm, SD = 0.33 for PIGD and TD patients, p = 0.37; mean rotation <0.1 degrees in both groups, with no difference between the group, p=0.82). Data were then spatially normalized into the standard Montreal Neurological Institute (MNI) space, using the standard SPM5 EPI template as a reference, and smoothed with a 8- mm, 3D-Gaussian filter. Linear trend removal and band-pass filtering between 0 and

0.08 Hz were performed.

We then carried out General linear Model (GLM) analyses for each patient with the affected putamen time series used as a repressor, and motion component, disease duration and age used as covariates. For the ROIs that showed significant correlation between GM volumes and PIGD or tremor scores, we extracted the level of connectivity with the putamen. For this, beta values were extracted for each patient by averaging the voxels within each ROI selected

4 Table e-1. Vascular risk factors.

PIGD-PD group TD-PD group P value (N=30) ((N=29

Hypertension 14 (46%) 17 (58.6%) 0.232

Diabetes 1 (3.3%) 5 (17.2%) 0.071 Hyper- 14 (46.4%) 10 (34.5%) 0.297 cholesterolemia

Smoking 3 (10%) 2 (6.9%) 0.641

Vascular Risk Index 0- 36.7% 0- 34.5% 1- 30% 1- 31.1% 0.782 (possible range: 0-4) 2- 30% 2- 24.1% 3- 3.3% 3- 10.3%

Table e-1. The presence or absence of vascular risk factors were determined based

on the clinical history. Entries are the numbers of subjects`that had a risk factor and in

parentheses the percent of the group that this number represents.

5 Figure legend: Figure e-1: Distribution of patients into the TD and PIGD subtype based on the original Jankovic et al. classification (square: PIGD; circle: TD) or based on classification used in this study (pink area: predominately-PIGD and cyan area: predominately-TD).

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