Replication and reliability of Parkinson's disease clinical subtypes.

BACKGROUND: We recently identified three distinct Parkinson's disease subtypes: "motor only" (predominant motor deficits with intact cognition and psychiatric function); "psychiatric & motor" (prominent psychiatric symptoms and moderate motor deficits); "cognitive & motor" (cognitive and motor deficits). OBJECTIVE: We used an independent cohort to replicate and assess reliability of these Parkinson's disease subtypes. METHODS: We tested our original subtype classification with an independent cohort (N = 100) of Parkinson's disease participants without dementia and the same comprehensive evaluations assessing motor, cognitive, and psychiatric function. Next, we combined the original (N = 162) and replication (N = 100) datasets to test the classification model with the full combined dataset (N = 262). We also generated 10 random split-half samples of the combined dataset to establish the reliability of the subtype classifications. Latent class analyses were applied to the replication, combined, and split-half samples to determine subtype classification. RESULTS: First, LCA supported the three-class solution - Motor Only, Psychiatric & Motor, and Cognitive & Motor- in the replication sample. Next, using the larger, combined sample, LCA again supported the three subtype groups, with the emergence of a potential fourth group defined by more severe motor deficits. Finally, split-half analyses showed that the three-class model also had the best fit in 13/20 (65%) split-half samples; two-class and four-class solutions provided the best model fit in five (25%) and two (10%) split-half replications, respectively. CONCLUSIONS: These results support the reproducibility and reliability of the Parkinson's disease behavioral subtypes of motor only, psychiatric & motor, and cognitive & motor groups.

PET Quantification of [18F]VAT in Human Brain and Its Test-Retest Reproducibility and Age Dependence.

Molecular imaging of brain vesicular acetylcholine transporter provides a biomarker to explore cholinergic systems in humans. We aimed to characterize the distribution of, and optimize methods to quantify, the vesicular acetylcholine transporter-specific tracer (-)-(1-(8-(2-[18F]fluoroethoxy)-3-hydroxy-1,2,3,4-tetrahydronaphthalen-2-yl)-piperidin-4-yl)(4-fluorophenyl)methanone ([18F]VAT) in the brain using PET. Methods: Fifty-two healthy participants aged 21-97 y had brain PET with [18F]VAT. [3H]VAT autoradiography identified brain areas devoid of specific binding in cortical white matter. PET image-based white matter reference region size, model start time, and duration were optimized for calculations of Logan nondisplaceable binding potential (BPND). Ten participants had 2 scans to determine test-retest variability. Finally, we analyzed age-dependent differences in participants. Results: [18F]VAT was widely distributed in the brain, with high striatal, thalamic, amygdala, hippocampal, cerebellar vermis, and regionally specific uptake in the cerebral cortex. [3H]VAT autoradiography-specific binding and PET [18F]VAT uptake were low in white matter. [18F]VAT SUVs in the white matter reference region correlated with age, requiring stringent erosion parameters. Logan BPND estimates stabilized using at least 40 min of data starting 25 min after injection. Test-retest variability had excellent reproducibility and reliability in repeat BPND calculations for 10 participants (putamen, 6.8%; r > 0.93). We observed age-dependent decreases in the caudate and putamen (multiple comparisons corrected) and in numerous cortical regions. Finally, we provide power tables to indicate potential mean differences that can be detected between 2 groups of participants. Conclusion: These results validate a reference region for BPND calculations and demonstrate the viability, reproducibility, and utility of using the [18F]VAT tracer in humans to quantify cholinergic pathways.

Neocortical Lewy Body Pathology Parallels Parkinson's Dementia, but Not Always.

OBJECTIVE: The objective of this study was to evaluate the relationship between Parkinson's disease (PD) with dementia and cortical proteinopathies in a large population of pathologically confirmed patients with PD. METHODS: We reviewed clinical data from all patients with autopsy data seen in the Movement Disorders Center at Washington University, St. Louis, between 1996 and 2019. All patients with a diagnosis of PD based on neuropathology were included. We used logistic regression and multivariate analysis of covariance (MANCOVA) to investigate the relationship between neuropathology and dementia. RESULTS: A total of 165 patients with PD met inclusion criteria. Among these, 128 had clinical dementia. Those with dementia had greater mean ages of motor onset and death but equivalent mean disease duration. The delay between motor symptom onset and dementia was 1 year or less in 14 individuals, meeting research diagnostic criteria for possible or probable dementia with Lewy bodies (DLB). Braak Lewy body stage was associated with diagnosis of dementia, whereas severities of Alzheimer's disease neuropathologic change (ADNC) and small vessel pathology did not. Pathology of individuals diagnosed with DLB did not differ significantly from that of other patients with PD with dementia. Six percent of individuals with PD and dementia did not have neocortical Lewy bodies; and 68% of the individuals with PD but without dementia did have neocortical Lewy bodies. INTERPRETATION: Neocortical Lewy bodies almost always accompany dementia in PD; however, they also appear in most PD patients without dementia. In some cases, dementia may occur in patients with PD without neocortical Lewy bodies, ADNC, or small vessel disease. Thus, other factors not directly related to these classic neuropathologic features may contribute to PD dementia. ANN NEUROL 2023;93:184-195.

Mitochondrial haplogroups and cognitive progression in Parkinson's disease.

Mitochondria are a culprit in the onset of Parkinson's disease, but their role during disease progression is unclear. Here we used Cox proportional hazards models to exam the effect of variation in the mitochondrial genome on longitudinal cognitive and motor progression over time in 4064 patients with Parkinson's disease. Mitochondrial macro-haplogroup was associated with reduced risk of cognitive disease progression in the discovery and replication population. In the combined analysis, patients with the super macro-haplogroup J, T, U# had a 41% lower risk of cognitive progression with P = 2.42 × 10-6 compared to those with macro-haplogroup H. Exploratory analysis indicated that the common mitochondrial DNA variant, m.2706A>G, was associated with slower cognitive decline with a hazard ratio of 0.68 (95% confidence interval 0.56-0.81) and P = 2.46 × 10-5. Mitochondrial haplogroups were not appreciably linked to motor progression. This initial genetic survival study of the mitochondrial genome suggests that mitochondrial haplogroups may be associated with the pace of cognitive progression in Parkinson's disease over time.

Proteinopathy and Longitudinal Cognitive Decline in Parkinson Disease.

BACKGROUND AND OBJECTIVES: People with Parkinson disease (PD) commonly experience cognitive decline, which may relate to increased α-synuclein, tau, and ß-amyloid accumulation. This study examines whether the different proteins predict longitudinal cognitive decline in PD. METHODS: All participants (PD n = 152, controls n = 52) were part of a longitudinal study and completed a lumbar puncture for CSF protein analysis (α-synuclein, total tau [tau], and ß-amyloid42 [ß-amyloid]), a ß-amyloid PET scan, and/or provided a blood sample for APOE genotype (ε4+, ε4-), which is a risk factor for ß-amyloid accumulation. Participants also had comprehensive, longitudinal clinical assessments of overall cognitive function and dementia status, as well as cognitive testing of attention, language, memory, and visuospatial and executive function. We used hierarchical linear growth models to examine whether the different protein metrics predict cognitive change and multivariate Cox proportional hazard models to predict time to dementia conversion. Akaike information criterion was used to compare models for best fit. RESULTS: Baseline measures of CSF ß-amyloid predicted decline for memory (p = 0.04) and overall cognitive function (p = 0.01). APOE genotypes showed a significant group (ε4+, ε4-) effect such that ε4+ individuals declined faster than ε4- individuals in visuospatial function (p = 0.03). Baseline ß-amyloid PET significantly predicted decline in all cognitive measures (all p ≤ 0.004). Neither baseline CSF α-synuclein nor tau predicted cognitive decline. All 3 ß-amyloid--related metrics (CSF, PET, APOE) also predicted time to dementia. Models with ß-amyloid PET as a predictor fit the data the best. DISCUSSION: Presence or risk of ß-amyloid accumulation consistently predicted cognitive decline and time to dementia in PD. This suggests that ß-amyloid has high potential as a prognostic indicator and biomarker for cognitive changes in PD.

Quantifying regional α -synuclein, amyloid ß, and tau accumulation in lewy body dementia.

OBJECTIVE: Parkinson disease (PD) is defined by the accumulation of misfolded α-synuclein (α-syn) in Lewy bodies and Lewy neurites. It affects multiple cortical and subcortical neuronal populations. The majority of people with PD develop dementia, which is associated with Lewy bodies in neocortex and referred to as Lewy body dementia (LBD). Other neuropathologic changes, including amyloid ß (Aß) and tau accumulation, occur in some LBD cases. We sought to quantify α-syn, Aß, and tau accumulation in neocortical, limbic, and basal ganglia regions. METHODS: We isolated insoluble protein from fresh frozen postmortem brain tissue samples for eight brains regions from 15 LBD, seven Alzheimer disease (AD), and six control cases. We measured insoluble α-syn, Aß, and tau with recently developed sandwich ELISAs. RESULTS: We detected a wide range of insoluble α-syn accumulation in LBD cases. The majority had substantial α-syn accumulation in most regions, and dementia severity correlated with neocortical α-syn. However, three cases had low neocortical levels that were indistinguishable from controls. Eight LBD cases had substantial Aß accumulation, although the mean Aß level in LBD was lower than in AD. The presence of Aß was associated with greater α-syn accumulation. Tau accumulation accompanied Aß in only one LBD case. INTERPRETATION: LBD is associated with insoluble α-syn accumulation in neocortical regions, but the relatively low neocortical levels in some cases suggest that other changes contribute to impaired function, such as loss of neocortical innervation from subcortical regions. The correlation between Aß and α-syn accumulation suggests a pathophysiologic relationship between these two processes.

Distinct progression patterns across Parkinson disease clinical subtypes.

OBJECTIVE: To examine specific symptom progression patterns and possible disease staging in Parkinson disease clinical subtypes. METHODS: We recently identified Parkinson disease clinical subtypes based on comprehensive behavioral evaluations, "Motor Only," "Psychiatric & Motor," and "Cognitive & Motor," which differed in dementia and mortality rates. Parkinson disease participants ("Motor Only": n = 61, "Psychiatric & Motor": n = 17, "Cognitive & Motor": n = 70) and controls (n = 55) completed longitudinal, comprehensive motor, cognitive, and psychiatric evaluations (average follow-up = 4.6 years). Hierarchical linear modeling examined group differences in symptom progression. A three-way interaction among time, group, and symptom duration (or baseline age, separately) was incorporated to examine disease stages. RESULTS: All three subtypes increased in motor dysfunction compared to controls. The "Motor Only" subtype did not show significant cognitive or psychiatric changes compared to the other two subtypes. The "Cognitive & Motor" subtype's cognitive dysfunction at baseline further declined compared to the other two subtypes, while also increasing in psychiatric symptoms. The "Psychiatric & Motor" subtype's elevated psychiatric symptoms at baseline remained steady or improved over time, with mild, steady decline in cognition. The pattern of behavioral changes and analyses for disease staging yielded no evidence for sequential disease stages. INTERPRETATION: Parkinson disease clinical subtypes progress in clear, temporally distinct patterns from one another, particularly in cognitive and psychiatric features. This highlights the importance of comprehensive clinical examinations as the order of symptom presentation impacts clinical prognosis.

Resting-state functional connectivity associated with gait characteristics in people with Parkinson's disease.

INTRODUCTION: Parkinson's disease (PD) is a movement disorder caused by dysfunction in the basal ganglia (BG). Clinically relevant gait deficits, such as decreased velocity and increased variability, may be caused by underlying neural dysfunction. Reductions in resting-state functional connectivity (rs-FC) between networks have been identified in PD compared to controls; however, the association between gait characteristics and rs-FC of brain networks in people with PD has not yet been explored. The present study aimed to investigate these associations. METHODS: Gait characteristics and rs-FC MRI data were collected for participants with PD (N = 50). Brain networks were identified from a set of seeds representing cortical, subcortical, and cerebellar regions. Gait outcomes were correlated with the strength of rs-FC within and between networks of interest. A stepwise regression analysis was also conducted to determine whether the rs-FC strength of brain networks, along with clinical motor scores, were predictive of gait characteristics. RESULTS: Gait velocity was associated with rs-FC within the visual network and between motor and cognitive networks, most notably BG-thalamus internetwork rs-FC. The stepwise regression analysis showed strength of BG-thalamus internetwork rs-FC and clinical motor scores were predictive of gait velocity. CONCLUSION: The results of the present study demonstrate gait characteristics are associated with functional organization of the brain at the network level, providing insight into the neural mechanisms of clinically relevant gait characteristics. This knowledge could be used to optimize the design of gait rehabilitation interventions for people with neurological conditions.

Functional Connectivity of Vermis Correlates with Future Gait Impairments in Parkinson's Disease.

BACKGROUND: Dysfunction of cerebellar vermis contributes to gait abnormalities in multiple conditions and may play a key role in gait impairment in Parkinson's disease (PD). OBJECTIVE: The purpose of this study was to investigate whether altered resting-state functional connectivity of the vermis relates to subsequent impairment of specific domains of gait in PD. METHODS: We conducted morphometric and resting-state functional connectivity MRI analyses contrasting 45 PD and 32 age-matched healthy participants. Quantitative gait measures were acquired with a GAITRite walkway at varying intervals after functional connectivity data acquisition. RESULTS: At baseline, PD participants had significantly altered functional connectivity between vermis and sensorimotor cortex compared with controls. Altered vermal functional connectivity with bilateral paracentral lobules correlated with subsequent measures of variability in stride length, step time, and single support time after controlling for confounding variables including the interval between imaging and gait measures. Similarly, altered functional connectivity between vermis and left sensorimotor cortex correlated with mean stride length and its variability. Vermis volume did not relate to any gait measure. PD participants did not differ from controls in vermis volume or cortical thickness at the site of significant regional clusters. Only altered lobule V:sensorimotor cortex functional connectivity correlated with subsequent gait measures in exploratory analyses involving all the other cerebellar lobules. CONCLUSIONS: These results demonstrate that abnormal vermal functional connectivity with sensorimotor cortex, in the absence of relevant vermal or cortical atrophy, correlates with subsequent gait impairment in PD. Our data reflect the potential of vermal functional connectivity as a novel imaging biomarker of gait impairment in PD. © 2021 International Parkinson and Movement Disorder Society.

Genome-wide survival study identifies a novel synaptic locus and polygenic score for cognitive progression in Parkinson's disease.

A key driver of patients' well-being and clinical trials for Parkinson's disease (PD) is the course that the disease takes over time (progression and prognosis). To assess how genetic variation influences the progression of PD over time to dementia, a major determinant for quality of life, we performed a longitudinal genome-wide survival study of 11.2 million variants in 3,821 patients with PD over 31,053 visits. We discover RIMS2 as a progression locus and confirm this in a replicate population (hazard ratio (HR) = 4.77, P = 2.78 × 10-11), identify suggestive evidence for TMEM108 (HR = 2.86, P = 2.09 × 10-8) and WWOX (HR = 2.12, P = 2.37 × 10-8) as progression loci, and confirm associations for GBA (HR = 1.93, P = 0.0002) and APOE (HR = 1.48, P = 0.001). Polygenic progression scores exhibit a substantial aggregate association with dementia risk, while polygenic susceptibility scores are not predictive. This study identifies a novel synaptic locus and polygenic score for cognitive disease progression in PD and proposes diverging genetic architectures of progression and susceptibility.

Resting-State Functional Connectivity Predicts STN DBS Clinical Response.

BACKGROUND: Deep brain stimulation of the subthalamic nucleus is a widely used adjunctive therapy for motor symptoms of Parkinson's disease, but with variable motor response. Predicting motor response remains difficult, and novel approaches may improve surgical outcomes as well as the understanding of pathophysiological mechanisms. The objective of this study was to determine whether preoperative resting-state functional connectivity MRI predicts motor response from deep brain stimulation of the subthalamic nucleus. METHODS: We collected preoperative resting-state functional MRI from 70 participants undergoing subthalamic nucleus deep brain stimulation. For this cohort, we analyzed the strength of STN functional connectivity with seeds determined by stimulation-induced (ON/OFF) 15 O H2 O PET regional cerebral blood flow differences in a partially overlapping group (n = 42). We correlated STN-seed functional connectivity strength with postoperative motor outcomes and applied linear regression to predict motor outcomes. RESULTS: Preoperative functional connectivity between the left subthalamic nucleus and the ipsilateral internal globus pallidus correlated with postsurgical motor outcomes (r = -0.39, P = 0.0007), with stronger preoperative functional connectivity relating to greater improvement. Left pallidal-subthalamic nucleus connectivity also predicted motor response to DBS after controlling for covariates. DISCUSSION: Preoperative pallidal-subthalamic nucleus resting-state functional connectivity predicts motor benefit from deep brain stimulation, although this should be validated prospectively before clinical application. These observations suggest that integrity of pallidal-subthalamic nucleus circuits may be critical to motor benefits from deep brain stimulation. © 2020 International Parkinson and Movement Disorder Society.

Functional genomic analyses uncover APOE-mediated regulation of brain and cerebrospinal fluid beta-amyloid levels in Parkinson disease.

Alpha-synuclein is the main protein component of Lewy bodies, the pathological hallmark of Parkinson's disease. However, genetic modifiers of cerebrospinal fluid (CSF) alpha-synuclein levels remain unknown. The use of CSF levels of amyloid beta1-42, total tau, and phosphorylated tau181 as quantitative traits in genetic studies have provided novel insights into Alzheimer's disease pathophysiology. A systematic study of the genomic architecture of CSF biomarkers in Parkinson's disease has not yet been conducted. Here, genome-wide association studies of CSF biomarker levels in a cohort of individuals with Parkinson's disease and controls (N = 1960) were performed. PD cases exhibited significantly lower CSF biomarker levels compared to controls. A SNP, proxy for APOE ε4, was associated with CSF amyloid beta1-42 levels (effect = - 0.5, p = 9.2 × 10-19). No genome-wide loci associated with CSF alpha-synuclein, total tau, or phosphorylated tau181 levels were identified in PD cohorts. Polygenic risk score constructed using the latest Parkinson's disease risk meta-analysis were associated with Parkinson's disease status (p = 0.035) and the genomic architecture of CSF amyloid beta1-42 (R2 = 2.29%; p = 2.5 × 10-11). Individuals with higher polygenic risk scores for PD risk presented with lower CSF amyloid beta1-42 levels (p = 7.3 × 10-04). Two-sample Mendelian Randomization revealed that CSF amyloid beta1-42 plays a role in Parkinson's disease (p = 1.4 × 10-05) and age at onset (p = 7.6 × 10-06), an effect mainly mediated by variants in the APOE locus. In a subset of PD samples, the APOE ε4 allele was associated with significantly lower levels of CSF amyloid beta1-42 (p = 3.8 × 10-06), higher mean cortical binding potentials (p = 5.8 × 10-08), and higher Braak amyloid beta score (p = 4.4 × 10-04). Together these results from high-throughput and hypothesis-free approaches converge on a genetic link between Parkinson's disease, CSF amyloid beta1-42, and APOE.

Regional, not global, functional connectivity contributes to isolated focal dystonia.

OBJECTIVE: To test the hypothesis that there is shared regional or global functional connectivity dysfunction in a large cohort of patients with isolated focal dystonia affecting different body regions compared to control participants. In this case-control study, we obtained resting-state MRI scans (three or four 7.3-minute runs) with eyes closed in participants with focal dystonia (cranial [17], cervical [13], laryngeal [18], or limb [10]) and age- and sex-matched controls. METHODS: Rigorous preprocessing for all analyses was performed to minimize effect of head motion during scan acquisition (dystonia n = 58, control n = 47 analyzed). We assessed regional functional connectivity by computing a seed-correlation map between putamen, pallidum, and sensorimotor cortex and all brain voxels. We assessed significant group differences on a cluster-wise basis. In a separate analysis, we applied 300 seed regions across the cortex, cerebellum, basal ganglia, and thalamus to comprehensively sample the whole brain. We obtained participant whole-brain correlation matrices by computing the correlation between seed average time courses for each seed pair. Weighted object-oriented data analysis assessed group-level whole-brain differences. RESULTS: Participants with focal dystonia had decreased functional connectivity at the regional level, within the striatum and between lateral primary sensorimotor cortex and ventral intraparietal area, whereas whole-brain correlation matrices did not differ between focal dystonia and control groups. Rigorous quality control measures eliminated spurious large-scale functional connectivity differences between groups. CONCLUSION: Regional functional connectivity differences, not global network level dysfunction, contributes to common pathophysiologic mechanisms in isolated focal dystonia. Rigorous quality control eliminated spurious large-scale network differences between patients with focal dystonia and control participants.

Parkinson disease clinical subtypes: key features & clinical milestones.

OBJECTIVES: Based on multi-domain classification of Parkinson disease (PD) subtypes, we sought to determine the key features that best differentiate subtypes and the utility of PD subtypes to predict clinical milestones. METHODS: Prospective cohort of 162 PD participants with ongoing, longitudinal follow-up. Latent class analysis (LCA) delineated subtypes based on score patterns across baseline motor, cognitive, and psychiatric measures. Discriminant analyses identified key features that distinguish subtypes at baseline. Cox regression models tested PD subtype differences in longitudinal conversion to clinical milestones, including deep brain stimulation (DBS), dementia, and mortality. RESULTS: LCA identified distinct subtypes: "motor only" (N = 63) characterized by primary motor deficits; "psychiatric & motor" (N = 17) characterized by prominent psychiatric symptoms and moderate motor deficits; "cognitive & motor" (N = 82) characterized by impaired cognition and moderate motor deficits. Depression, executive function, and apathy best discriminated subtypes. Since enrollment, 22 had DBS, 48 developed dementia, and 46 have died. Although there were no subtype differences in rate of DBS, dementia occurred at a higher rate in the "cognitive & motor" subtype. Surprisingly, mortality risk was similarly elevated for both "cognitive & motor" and "psychiatric & motor" subtypes compared to the "motor only" subtype (relative risk = 3.15, 2.60). INTERPRETATION: Psychiatric and cognitive features, rather than motor deficits, distinguish clinical PD subtypes and predict greater risk of subsequent dementia and mortality. These results emphasize the value of multi-domain assessments to better characterize clinical variability in PD. Further, differences in dementia and mortality rates demonstrate the prognostic utility of PD subtypes.

Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivity.

Denoising fMRI data requires assessment of frame-to-frame head motion and removal of the biases motion introduces. This is usually done through analysis of the parameters calculated during retrospective head motion correction (i.e., 'motion' parameters). However, it is increasingly recognized that respiration introduces factitious head motion via perturbations of the main (B0) field. This effect appears as higher-frequency fluctuations in the motion parameters (>0.1 â€‹Hz, here referred to as 'HF-motion'), primarily in the phase-encoding direction. This periodicity can sometimes be obscured in standard single-band fMRI (TR 2.0-2.5 â€‹s) due to aliasing. Here we examined (1) how prevalent HF-motion effects are in seven single-band datasets with TR from 2.0 to 2.5 â€‹s and (2) how HF-motion affects functional connectivity. We demonstrate that HF-motion is more common in older adults, those with higher body mass index, and those with lower cardiorespiratory fitness. We propose a low-pass filtering approach to remove the contamination of high frequency effects from motion summary measures, such as framewise displacement (FD). We demonstrate that in most datasets this filtering approach saves a substantial amount of data from FD-based frame censoring, while at the same time reducing motion biases in functional connectivity measures. These findings suggest that filtering motion parameters is an effective way to improve the fidelity of head motion estimates, even in single band datasets. Particularly large data savings may accrue in datasets acquired in older and less fit participants.

Proteinopathy and longitudinal changes in functional connectivity networks in Parkinson disease.

OBJECTIVE: To evaluate resting-state functional connectivity as a potential prognostic biomarker of Parkinson disease (PD) progression. The study examined longitudinal changes in cortical resting-state functional connectivity networks in participants with PD compared to controls as well as in relation to baseline protein measures and longitudinal clinical progression. METHODS: Individuals with PD without dementia (n = 64) and control participants (n = 27) completed longitudinal resting-state MRI scans and clinical assessments including full neuropsychological testing after overnight withdrawal of PD medications ("off"). A total of 55 participants with PD and 20 control participants also completed baseline ß-amyloid PET scans and lumbar punctures for CSF protein levels of α-synuclein, ß-amyloid, and tau. Longitudinal analyses were conducted with multilevel growth curve modeling, a type of mixed-effects model. RESULTS: Functional connectivity within the sensorimotor network and the interaction between the dorsal attention network with the frontoparietal control network decreased significantly over time in participants with PD compared to controls. Baseline CSF α-synuclein protein levels predicted decline in the sensorimotor network. The longitudinal decline in the dorsal attention-frontoparietal internetwork strength correlated with the decline in cognitive function. CONCLUSIONS: These results indicate that α-synuclein levels may influence longitudinal declines in motor-related functional connectivity networks. Further, the interaction between cortical association networks declines over time in PD prior to dementia onset and may serve as a prognostic marker for the development of dementia.

Little Change in Functional Brain Networks Following Acute Levodopa in Drug-Naïve Parkinson's Disease.

OBJECTIVE: The objective of this study was to investigate the effects of levodopa on functional brain networks in Parkinson's disease. METHODS: We acquired resting state functional magnetic resonance imaging in 30 drug-naïve participants with Parkinson's disease and 20 age-matched healthy controls. Each participant was studied following administration of a single oral dose of either levodopa or placebo in a randomized, double-blind, crossover design. RESULTS: The greatest observed differences in functional connectivity were between Parkinson's disease versus control participants, independent of pharmacologic intervention. By contrast, the effects of levodopa were much smaller and detectable only in the Parkinson's disease group. Moreover, although levodopa administration in the Parkinson's disease group measurably improved motor performance, it did not increase the similarity of functional connectivity in Parkinson's disease to the control group. CONCLUSIONS: We found that a single, small dose of levodopa did not normalize functional connectivity in drug-naïve Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society.

Cognitive correlates of cerebellar resting-state functional connectivity in Parkinson disease.

OBJECTIVE: To investigate in a cross-sectional study the contributions of altered cerebellar resting-state functional connectivity (FC) to cognitive impairment in Parkinson disease (PD). METHODS: We conducted morphometric and resting-state FC-MRI analyses contrasting 81 participants with PD and 43 age-matched healthy controls using rigorous quality assurance measures. To investigate the relationship of cerebellar FC to cognitive status, we compared participants with PD without cognitive impairment (Clinical Dementia Rating [CDR] scale score 0, n = 47) to participants with PD with impaired cognition (CDR score ≥0.5, n = 34). Comprehensive measures of cognition across the 5 cognitive domains were assessed for behavioral correlations. RESULTS: The participants with PD had significantly weaker FC between the vermis and peristriate visual association cortex compared to controls, and the strength of this FC correlated with visuospatial function and global cognition. In contrast, weaker FC between the vermis and dorsolateral prefrontal cortex was found in the cognitively impaired PD group compared to participants with PD without cognitive impairment. This effect correlated with deficits in attention, executive functions, and global cognition. No group differences in cerebellar lobular volumes or regional cortical thickness of the significant cortical clusters were observed. CONCLUSION: These results demonstrate a correlation between cerebellar vermal FC and cognitive impairment in PD. The absence of significant atrophy in cerebellum or relevant cortical areas suggests that this could be related to local pathophysiology such as neurotransmitter dysfunction.

Detecting associations between intact connectomes and clinical covariates using recursive partitioning object-oriented data analysis.

Many neuroscientists are interested in how connectomes (graphical representations of functional connectivity between areas of the brain) change in relation to covariates. In statistics, changes like this are analyzed using regression, where the outcomes or dependent variables are regressed onto the covariates. However, when the outcome is a complex object, such as connectome graphs, classical regression models cannot be used. The regression approach developed here to work with complex graph outcomes combines recursive partitioning with the Gibbs distribution. We will only discuss the application to connectomes, but the method is generally applicable to any graphical outcome. The method, called Gibbs-RPart, partitions the covariate space into a set of nonoverlapping regions such that the connectomes within regions are more similar than they are to the connectomes in other regions. This paper extends the object-oriented data analysis paradigm for graph-valued data based on the Gibbs distribution, which we have applied previously to hypothesis testing to compare populations of connectomes from distinct groups (see the work of La Rosa et al).

Emergent Functional Network Effects in Parkinson Disease.

The hallmark pathology underlying Parkinson disease (PD) is progressive synucleinopathy, beginning in caudal brainstem that later spreads rostrally. However, the primarily subcortical pathology fails to account for the wide spectrum of clinical manifestations in PD. To reconcile these observations, resting-state functional connectivity (FC) can be used to examine dysfunction across distributed brain networks. We measured FC in a large, single-site study of nondemented PD (N = 107; OFF medications) and healthy controls (N = 46) incorporating rigorous quality control measures and comprehensive sampling of cortical, subcortical and cerebellar regions. We employed novel statistical approaches to determine group differences across the entire connectome, at the network-level, and for select brain regions. Group differences respected well-characterized network delineations producing a striking "block-wise" pattern of network-to-network effects. Surprisingly, these results demonstrate that the greatest FC differences involve sensorimotor, thalamic, and cerebellar networks, with notably smaller striatal effects. Split-half replication demonstrates the robustness of these results. Finally, block-wise FC correlations with behavior suggest that FC disruptions may contribute to clinical manifestations in PD. Overall, these results indicate a concerted breakdown of functional network interactions, remote from primary pathophysiology, and suggest that FC deficits in PD are related to emergent network-level phenomena rather than focal pathology.