Sex, myelin, and clinical characteristics of Parkinson's disease.

Objective: To determine if there are sex differences in myelin in Parkinson's disease, and whether these explain some of the previously-described sex differences in clinical presentation. Methods: Thirty-three subjects (23 males, 10 females) with Parkinson's disease underwent myelin water fraction (MWF) imaging, an MRI scanning technique of in vivo myelin content. MWF of 20 white matter regions of interest (ROIs) were assessed. Motor symptoms were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS). Principal component analysis, logistic and multiple linear regressions, and t-tests were used to determine which white matter ROIs differed between sexes, the clinical features associated with these myelin changes, and if overall MWF and MWF laterality differed between males and females. Results: Consistent with prior reports, tremor and bradykinesia were more likely seen in females, whereas rigidity and axial symptoms were more likely seen in males in our cohort. MWF of the thalamic radiation, cingulum, cingulum hippocampus, inferior fronto-occipital fasciculi, inferior longitudinal fasciculi, and uncinate were significant in predicting sex. Overall MWF and asymmetry of MWF was greater in males. MWF differences between sexes were associated with tremor symptomatology and asymmetry of motor performance. Conclusion: Sex differences in myelin are associated with tremor and asymmetry of motor presentation. While preliminary, our results suggest that further investigation of the role of biological sex in myelin pathology and clinical presentation in Parkinson's disease is warranted.

Patient-specific models link neurotransmitter receptor mechanisms with motor and visuospatial axes of Parkinson's disease.

Parkinson's disease involves multiple neurotransmitter systems beyond the classical dopaminergic circuit, but their influence on structural and functional alterations is not well understood. Here, we use patient-specific causal brain modeling to identify latent neurotransmitter receptor-mediated mechanisms contributing to Parkinson's disease progression. Combining the spatial distribution of 15 receptors from post-mortem autoradiography with 6 neuroimaging-derived pathological factors, we detect a diverse set of receptors influencing gray matter atrophy, functional activity dysregulation, microstructural degeneration, and dendrite and dopaminergic transporter loss. Inter-individual variability in receptor mechanisms correlates with symptom severity along two distinct axes, representing motor and psychomotor symptoms with large GABAergic and glutamatergic contributions, and cholinergically-dominant visuospatial, psychiatric and memory dysfunction. Our work demonstrates that receptor architecture helps explain multi-factorial brain re-organization, and suggests that distinct, co-existing receptor-mediated processes underlie Parkinson's disease.

Neuroimaging signatures predicting motor improvement to focused ultrasound subthalamotomy in Parkinson's disease.

Subthalamotomy using transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) is a novel and promising treatment for Parkinson's Disease (PD). In this study, we investigate if baseline brain imaging features can be early predictors of tcMRgFUS-subthalamotomy efficacy, as well as which are the post-treatment brain changes associated with the clinical outcomes. Towards this aim, functional and structural neuroimaging and extensive clinical data from thirty-five PD patients enrolled in a double-blind tcMRgFUS-subthalamotomy clinical trial were analyzed. A multivariate cross-correlation analysis revealed that the baseline multimodal imaging data significantly explain (P < 0.005, FWE-corrected) the inter-individual variability in response to treatment. Most predictive features at baseline included neural fluctuations in distributed cortical regions and structural integrity in the putamen and parietal regions. Additionally, a similar multivariate analysis showed that the population variance in clinical improvements is significantly explained (P < 0.001, FWE-corrected) by a distributed network of concurrent functional and structural brain changes in frontotemporal, parietal, occipital, and cerebellar regions, as opposed to local changes in very specific brain regions. Overall, our findings reveal specific quantitative brain signatures highly predictive of tcMRgFUS-subthalamotomy responsiveness in PD. The unanticipated weight of a cortical-subcortical-cerebellar subnetwork in defining clinical outcome extends the current biological understanding of the mechanisms associated with clinical benefits.

Multivariate genomic and transcriptomic determinants of imaging-derived personalized therapeutic needs in Parkinson's disease.

Due to the marked interpersonal neuropathologic and clinical heterogeneity of Parkinson's disease (PD), current interventions are not personalized and fail to benefit all patients. Furthermore, we continue to lack well-established methods and clinical tests to tailor interventions at the individual level in PD. Here, we identify the genetic determinants of individual-tailored treatment needs derived from longitudinal multimodal neuroimaging data in 294 PD patients (PPMI data). Advanced multivariate statistical analysis revealed that both genomic and blood transcriptomic data significantly explain (P < 0.01, FWE-corrected) the interindividual variability in therapeutic needs associated with dopaminergic, functional, and structural brain reorganization. We confirmed a high overlap between the identified highly predictive molecular pathways and determinants of levodopa clinical responsiveness, including well-known (Wnt signaling, angiogenesis, dopaminergic activity) and recently discovered (immune markers, gonadotropin-releasing hormone receptor) pathways/components. In addition, the observed strong correspondence between the identified genomic and baseline-transcriptomic determinants of treatment needs/response supports the genome's active role at the time of patient evaluation (i.e., beyond individual genetic predispositions at birth). This study paves the way for effectively combining genomic, transcriptomic and neuroimaging data for implementing successful individually tailored interventions in PD and extending our pathogenetic understanding of this multifactorial and heterogeneous disorder.

A Multi-sequence MRI Study in Parkinson's Disease: Association Between Rigidity and Myelin.

BACKGROUND: The pathophysiology of rigidity in Parkinson's disease (PD) is poorly understood. Multi-sequence functional and structural brain MRI may further clarify the origin of this clinical characteristic. PURPOSE: To examine both joint and unique relationships of MRI-based functional and structural imaging modalities to rigidity and other clinical features of PD. STUDY TYPE: Retrospective cross-sectional study. POPULATION: 31 PD subjects (aged 68.0 ± 5.9 years, 21 males) with average disease duration 9.3 ± 5.4 years. FIELD STRENGTH/SEQUENCE: Multi-echo GRASE, diffusion-weighted echo planar imaging (EPI), and blood oxygen level dependent contrast EPI T2*-weighted sequences on a 3T scanner. ASSESSMENT: Myelin water fraction (MWF) and fractional anisotropy (FA) of 20 white-matter regions of interest (ROIs), and functional connectivity derived from resting-state fMRI among 56 ROIs were assessed. The Unified Parkinson's Disease Rating Scale-Part III, Montreal Cognitive Assessment, Beck Depression Index, and Apathy Rating Scales were used to assess motor and non-motor symptoms. STATISTICAL TESTS: Multiset canonical correlation analysis (MCCA) and canonical correlation analysis (CCA) were utilized to examine the joint and unique relationships of multiple imaging measures with clinical symptoms of PD. A permutation test was used to determine statistical significance (P < 0.05). RESULTS: MCCA revealed a single significant component jointly linking MWF, FA, and functional connectivity to age, bradykinesia, and leg agility, non-motor symptoms of cognition, depression, and apathy, but not rigidity (P = 0.77), tremor (P = 0.50 and 0.67 on the left and right side), or sex (P = 0.54). After controlling for this joint component, CCA found a unique significant association between MWF and rigidity, but no other associations were detected, including with FA (P = 0.87). DATA CONCLUSION: MWF, FA, and functional connectivity can serve as multi-sequence imaging markers to characterize many PD symptoms. However, rigidity in PD is additionally associated with widespread myelin changes. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 3.

Personalized brain models identify neurotransmitter receptor changes in Alzheimer's disease.

Alzheimer's disease involves many neurobiological alterations from molecular to macroscopic spatial scales, but we currently lack integrative, mechanistic brain models characterizing how factors across different biological scales interact to cause clinical deterioration in a way that is subject-specific or personalized. As important signalling molecules and mediators of many neurobiological interactions, neurotransmitter receptors are promising candidates for identifying molecular mechanisms and drug targets in Alzheimer's disease. We present a neurotransmitter receptor-enriched multifactorial brain model, which integrates spatial distribution patterns of 15 neurotransmitter receptors from post-mortem autoradiography with multiple in vivo neuroimaging modalities (tau, amyloid-ß and glucose PET, and structural, functional and arterial spin labelling MRI) in a personalized, generative, whole-brain formulation. In a heterogeneous aged population (n = 423, ADNI data), models with personalized receptor-neuroimaging interactions showed a significant improvement over neuroimaging-only models, explaining about 70% (±20%) of the variance in longitudinal changes to the six neuroimaging modalities. In Alzheimer's disease patients (n = 25, ADNI data), receptor-imaging interactions explained up to 39.7% (P < 0.003, family-wise error-rate-corrected) of inter-individual variability in cognitive deterioration, via an axis primarily affecting executive function. Notably, based on their contribution to the clinical severity in Alzheimer's disease, we found significant functional alterations to glutamatergic interactions affecting tau accumulation and neural activity dysfunction and GABAergic interactions concurrently affecting neural activity dysfunction, amyloid and tau distributions, as well as significant cholinergic receptor effects on tau accumulation. Overall, GABAergic alterations had the largest effect on cognitive impairment (particularly executive function) in our Alzheimer's disease cohort (n = 25). Furthermore, we demonstrate the clinical applicability of this approach by characterizing subjects based on individualized 'fingerprints' of receptor alterations. This study introduces the first robust, data-driven framework for integrating several neurotransmitter receptors, multimodal neuroimaging and clinical data in a flexible and interpretable brain model. It enables further understanding of the mechanistic neuropathological basis of neurodegenerative progression and heterogeneity, and constitutes a promising step towards implementing personalized, neurotransmitter-based treatments.

Integrating molecular, histopathological, neuroimaging and clinical neuroscience data with NeuroPM-box.

Understanding and treating heterogeneous brain disorders requires specialized techniques spanning genetics, proteomics, and neuroimaging. Designed to meet this need, NeuroPM-box is a user-friendly, open-access, multi-tool cross-platform software capable of characterizing multiscale and multifactorial neuropathological mechanisms. Using advanced analytical modeling for molecular, histopathological, brain-imaging and/or clinical evaluations, this framework has multiple applications, validated here with synthetic (N > 2900), in-vivo (N = 911) and post-mortem (N = 736) neurodegenerative data, and including the ability to characterize: (i) the series of sequential states (genetic, histopathological, imaging or clinical alterations) covering decades of disease progression, (ii) concurrent intra-brain spreading of pathological factors (e.g., amyloid, tau and alpha-synuclein proteins), (iii) synergistic interactions between multiple biological factors (e.g., toxic tau effects on brain atrophy), and (iv) biologically-defined patient stratification based on disease heterogeneity and/or therapeutic needs. This freely available toolbox ( neuropm-lab.com/neuropm-box.html ) could contribute significantly to a better understanding of complex brain processes and accelerating the implementation of Precision Medicine in Neurology.

Inherent spatial structure in myelin water fraction maps.

Myelin water fraction (MWF) images in brain tend to be spatially noisy with unknown or no apparent spatial patterns structure, so values are therefore typically averaged over large white matter (WM) volumes. We investigated the existence of an inherent spatial structure in MWF maps and explored the benefits of examining MWF values along diffusion tensor imaging (DTI)-derived white matter tracts. We compared spatial anisotropy between MWF and the more widely-used fractional anisotropy (FA) measure. Sixteen major white matter fibre bundles were extracted based on DTI data from 41 healthy subjects. MWF coefficients of variation (CoV) were computed in sub-segments along each fibre tract and compared to MWF CoVs from the surrounding "tubes" - i.e. voxels just exterior to the tract - of each segment. We further assessed the consistency of the MWF along fibre bundles across subjects and investigated the benefit of examining MWF values in sections along each fibre bundle rather than integrating over the whole tract. CoVs of MWF and FA were lower in fibre bundles compared to their enclosing tubes in all investigated tracts. Both measures possessed a spatial gradient of CoV that was smaller aligned along, compared to perpendicular to, the fibre bundles. All WM tracts showed MWF profiles along their trajectory that were consistent across subjects and were more accurate than the mean overall fibre MWF value in estimating ages of the subjects. We conclude that, although less obvious visually, the spatial MWF distribution in white matter consistently follows a distinct pattern along underlying fibre bundles across subjects. Assessing MWF in sections along white matter tracts may provide a sensitive and robust way to assess myelin across subjects.

Data fusion detects consistent relations between non-lesional white matter myelin, executive function, and clinical characteristics in multiple sclerosis.

We examined the influence of dysfunctional, non-lesional white matter on cognitive performance in multiple sclerosis (MS). Forty-six MS subjects were assessed using MRI-based myelin water imaging (MWI), and average myelin water fraction (MWF) values across 20 white matter regions of interest (ROIs) were determined. A data-fusion method, multiset canonical correlation analysis (MCCA), was used to investigate the multivariate, deterministic joint relations between MWF, executive function, and demographic and clinical characteristics. MCCA revealed one significant component (p = 0.009) which consisted of three linked profiles, with a pairwise correlation between the MWF and cognitive profiles of r = 0.37, a correlation between MWF and demographics profiles of r = 0.31, and between cognitive and demographics profiles r = 0.64. White matter ROIs representing long-range intra-hemispheric tracts and ROIs connecting the two hemispheres were positively related through their individual profiles to overall cognitive performance, education and female gender, while age, EDSS, and disease duration were related negatively. Surprisingly, lesions within the ROIs had a negligible effect on overall relations between imaging, cognitive, and demographic variables. These findings indicate that there is a strong association between a pattern of MWF values and cognitive performance in MS, which is modulated by age, education, and disease severity. Moreover, this consistent relation involves multiple white matter regions and is separate from the influence of lesions.

Altered EEG alpha and theta oscillations characterize apathy in Parkinson's disease during incentivized movement.

Apathy is a common non-motor symptom of Parkinson's disease (PD) that is difficult to quantify and poorly understood. Some studies have used incentivized motor tasks to assess apathy, as the condition is often associated with a reduction in motivated behavior. Normally event-related desynchronization, a reduction of power in specific frequency bands, is observed in the motor cortex during the peri-movement period. Also, alpha (8-12 Hz) and theta (4-7 Hz) oscillations are sensitive to rewards that are closely related to motivational states however these oscillations have not been widely investigated in relation to apathy in PD. Using EEG recordings, we investigated the neural oscillatory characteristics of apathy in PD during an incentivized motor task with interleaved rest periods. Apathetic and non-apathetic PD subjects on dopaminergic medication and healthy control subjects were instructed to squeeze a hand grip device for a monetary reward proportional to the subject's grip force and the monetary value attributed to that trial. Apathetic PD subjects exhibited higher alpha and theta powers in the pre-trial baseline rest period compared to non-apathetic PD subjects and healthy subjects. Further, we found that both resting power and relative power in alpha and theta bands during incentivized movement predicted PD subjects' apathy scores. Our results suggest that apathetic PD patients may need to overcome greater baseline alpha and theta oscillatory activity in order to facilitate incentivized movement. Clinically, resting alpha and theta power as well as alpha and theta event-related desynchronization during movement may serve as potential neural markers for apathy severity in PD.

White matter myelin profiles linked to clinical subtypes of Parkinson's disease.

BACKGROUND: White matter (WM) microstructural integrity is important for effective brain functioning and alterations have been shown in many neurodegenerative diseases. PURPOSE: To investigate WM myelin profiles and their relation to clinical features of Parkinson's disease (PD). STUDY TYPE: Retrospective cross-sectional. POPULATION: In all, 29 PD subjects and 15 healthy controls. FIELD STRENGTH/SEQUENCE: Multiecho GRASE with 10 msec echo spacing and echo planar imaging (EPI) diffusion-weighted (b-value = 700 with 32 gradient directions) on a 3T scanner. ASSESSMENT: Myelin water fraction (MWF) and fractional anisotropy (FA) across 20 WM regions of interest (ROIs) were compared between groups. Partial least squares (PLS) was used to associate MWF and FA with clinical and behavioral measures. STATISTICAL TESTS: Group comparisons were done using two-sample t-tests. PLS was assessed with permutation tests. Bootstrapping was used to investigate the robustness of imaging features. RESULTS: No group differences in myelin content could be detected with univariate tests. A three-component PLS model linked MWF profiles to clinical phenotypes but no FA profiles. The three components appeared to follow along broad motor/nonmotor subtypes of "akinetic-rigid," "tremor-predominant," and "depression/apathy" subtypes, respectively. The first component showed associations between overall motor scores (r = -0.43, P = 0.0196) and cognitive performance (r = 0.44, P = 0.0171) with interhemispheric and long-range association fibers. A second component linked overall motor scores (r = -0.58, P = 0.0009) and tremor scores (r = -0.48, P = 0.0091) to predominantly projection fibers. The last component related depression (r = -0.60, P = 0.0006) and apathy scores (r = -0.66, P = 0.0001 and r = -49, P = 0.0072) to a mixture of association and projection fibers. DATA CONCLUSION: MWF was robustly linked to distinct clinical subtypes of PD and may serve as an additional tool to characterize the disease. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:164-174.

Cognitive Profiles and Hub Vulnerability in Parkinson's Disease.

The clinicopathological correlations between aspects of cognition, disease severity and imaging in Parkinson's Disease (PD) have been unclear. We studied cognitive profiles, demographics, and functional connectivity patterns derived from resting-state fMRI data (rsFC) in 31 PD subjects from the Parkinson's Progression Markers Initiative (PPMI) database. We also examined rsFC from 19 healthy subjects (HS) from the Pacific Parkinson's Research Centre. Graph theoretical measures were used to summarize the rsFC patterns. Canonical correlation analysis (CCA) was used to relate separate cognitive profiles in PD that were associated with disease severity and demographic measures as well as rsFC network measures. The CCA model relating cognition to demographics suggested female gender and education supported cognitive function in PD, age and depression scores were anti-correlated with overall cognition, and UPDRS had little influence on cognition. Alone, rsFC global network measures did not significantly differ between PD and controls, yet some nodal network measures, such as network segregation, were distinguishable between PD and HS in cortical "hub" regions. The CCA model relating cognition to rsFC global network values, which was not related to the other CCA model relating cognition to demographic information, suggested modularity, rich club coefficient, and transitivity was also broadly related to cognition in PD. Our results suggest that education, aging, comorbidity, and gender impact cognition more than overall disease severity in PD. Cortical "hub" regions are vulnerable in PD, and impairments of processing speed, attention, scanning abilities, and executive skills are related to enhanced functional segregation seen in PD.

Orientation Dependent MR Signal Decay Differentiates between People with MS, Their Asymptomatic Siblings and Unrelated Healthy Controls.

R2* relaxometry of the brain is a quantitative magnetic resonance technique which is influenced by iron and myelin content across different brain regions. Multiple sclerosis (MS) is a common inflammatory, demyelinating disease affecting both white and grey matter regions of the CNS. Using R2*, increased iron deposition has been described in deep gray matter of MS patients. Iron accumulation might promote oxidative stress in the brain, which can lead to cell death and neurodegeneration. However, recent histological work indicates that iron may be reduced within the normal appearing white matter (WM) in MS. In the present study we analyzed the R2* signal across the white matter in 39 patients with MS, 31 asymptomatic age matched siblings of patients and 30 age-matched controls. The measurement of R2* in white matter is affected by the signal's dependency on white matter fibre orientation with respect to the main magnetic field which can be accounted using diffusion tensor imaging. We observed a clear separation of the three study groups in R2*. The values in the MS group were significantly lower compared to the siblings and controls, while the siblings group presented with significantly higher R2* values than both unrelated healthy controls and patients. Furthermore, we found significantly decreased normal-appearing white matter R2* values in patients with more severe disease course. Angle resolved analysis of R2* improves the sensitivity for detecting subtle differences in WM R2* compared to standard histogram based analyses. Our findings suggest that the decreased R2* values in MS are due to diffuse tissue damage and decreased myelin in the normal appearing and diffusely abnormal WM. The increased R2* in unaffected siblings may identify a predisposition to increased iron and the potential for oxidative stress as a risk factor for developing MS.