Brain atrophy progression in Parkinson's disease is shaped by connectivity and local vulnerability

Brain atrophy has been reported in the early stages of Parkinson's disease, but there have been few longitudinal studies. How intrinsic properties of the brain, such as anatomical connectivity, local cell-type distribution and gene expression combine to determine the pattern of disease progression also remains unknown. One hypothesis proposes that the disease stems from prion-like propagation of misfolded alpha-synuclein via the connectome that might cause varying degrees of tissue damage based on local properties. Here, we used MRI data from the Parkinson Progression Markers Initiative to map the progression of brain atrophy over 1, 2 and 4 years compared with baseline. We derived atrophy maps for four time points using deformation-based morphometry applied to T₁-weighted MRI from 120 de novo Parkinson's disease patients, 74 of whom had imaging at all four time points (50 Men: 24 Women) and 157 healthy control participants (115 Men: 42 Women). In order to determine factors that may influence neurodegeneration, we related atrophy progression to brain structural and functional connectivity, cell-type expression and gene ontology enrichment analyses. After regressing out the expected age and sex effects associated with normal ageing, we found that atrophy significantly progressed over 2 and 4 years in the caudate, nucleus accumbens, hippocampus and posterior cortical regions. This progression was shaped by both structural and functional brain connectivity. Also, the progression of atrophy was more pronounced in regions with a higher expression of genes related to synapses and was inversely related to the prevalence of oligodendrocytes and endothelial cells. In sum, we demonstrate that the progression of atrophy in Parkinson's disease is in line with the prion-like propagation hypothesis of alpha-synuclein and provide evidence that synapses may be especially vulnerable to synucleinopathy. In addition to identifying vulnerable brain regions, this study reveals different factors that may be implicated in the neurotoxic mechanisms leading to progression in Parkinson's disease. All brain maps generated here are available on request.

Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression

Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clustering that simultaneously: 1) incorporates whole brain data, 2) leverages unequal visits per individual, 3) compares clusters with a control group, 4) allows for study confounding effects, 5) provides cluster visualization, 6) measures clustering uncertainty. We used amyloid-β positive AD and negative healthy subjects, three longitudinal structural magnetic resonance imaging scans (cortical thickness and subcortical volume) over two years. We found three distinct longitudinal AD brain atrophy patterns: one typical diffuse pattern (n=34, 47.2%), and two atypical patterns: minimal atrophy (n=23 31.9%) and hippocampal sparing (n=9, 12.5%). We also identified outliers (n=3, 4.2%) and observations with uncertain classification (n=3, 4.2%). The clusters differed not only in regional distributions of atrophy at baseline, but also longitudinal atrophy progression, age at AD onset, and cognitive decline. A framework for the longitudinal assessment of variability in cohorts with several neuroimaging measures was successfully developed. We believe this framework may aid in disentangling distinct subtypes of AD from disease staging.

A Fully Automated Pipeline for Normative Atrophy in Patients with Neurodegenerative Disease

Introduction

Volumetric image analysis to detect progressive brain tissue loss in patients with multiple sclerosis (MS) has recently been suggested as a promising marker for "no evidence of disease activity." Software packages for longitudinal whole-brain volume analysis in individual patients are already in clinical use; however, most of these methods have omitted region-based analysis. Here, we suggest a fully automatic analysis pipeline based on the free software packages FSL and FreeSurfer.

Materials and methods

Fifty-five T1-weighted magnetic resonance imaging (MRI) datasets of five patients with confirmed relapsing-remitting MS and mild to moderate disability were longitudinally analyzed compared to a morphometric reference database of 323 healthy controls (HCs). After lesion filling, the volumes of brain segmentations and morphometric parameters of cortical parcellations were automatically screened for global and regional abnormalities. Error margins and artifact probabilities of regional morphometric parameters were estimated. Linear models were fitted to the series of follow-up MRIs and checked for consistency with cross-sectional aging in HCs.

Results

As compared to leave-one-out cross-validation in a subset of the control dataset, anomaly detection rates were highly elevated in MRIs of two patients. We detected progressive volume changes that were stronger than expected compared to normal aging in 4/5 patients. In individual patients, we also identified stronger than expected regional decreases of subcortical gray matter, of cortical thickness, and areas of reducing gray-white contrast over time.

Conclusion

Statistical comparison with a large normative database may provide complementary and rater independent quantitative information about regional morphological changes related to disease progression or drug-related disease modification in individual patients. Regional volume loss may also be detected in clinically stable patients.

Progression of regional atrophy in the left hemisphere contributes to clinical and cognitive deterioration in multiple sclerosis: A 5-year study

In this longitudinal study, we investigated the regional patterns of focal lesions accumulation, and gray (GM) and white matter (WM) atrophy progression over a five-year follow-up (FU) in multiple sclerosis (MS) patients and their association with clinical and cognitive deterioration. Neurological, neuropsychological and brain MRI (dual-echo and 3D T1-weighted sequences) assessments were prospectively performed at baseline (T0) and after a median FU of 4.9 years from 66 MS patients (including relapse-onset and primary progressive MS) and 16 matched controls. Lesion probability maps were obtained. Longitudinal changes of GM and WM volumes and their association with clinical and cognitive deterioration were assessed using tensor-based morphometry and SPM12. At FU, 36/66 (54.5%) MS patients showed a significant disability worsening, 14/66 (21.2%) evolved to a worse clinical phenotype, and 18/63 (28.6%) developed cognitive deterioration. At T0, compared to controls, MS patients showed a widespread pattern of GM atrophy, involving cortex, deep GM and cerebellum, and atrophy of the majority of WM tracts, which further progressed at FU (P < 0.001, uncorrected). Compared to stable patients, those with clinical and cognitive worsening showed a left-lateralized pattern of GM and WM atrophy, involving deep GM, fronto-temporo-parieto-occipital regions, cerebellum, and several WM tracts (P < 0.001, uncorrected).GM and WM atrophy of relevant brain regions occur in MS after 5 years. A different vulnerability of the two brain hemispheres to irreversible structural damage may be among the factors contributing to clinical and cognitive worsening in these patients. Hum Brain Mapp 38:5648-5665, 2017. © 2017 Wiley Periodicals, Inc.

Mapping the Progression of Atrophy in Early- and Late-Onset Alzheimer's Disease

The term early-onset Alzheimer's disease (EOAD) identifies patients who meet criteria for AD, but show onset of symptoms before the age of 65. We map progression of gray matter atrophy in EOAD patients compared to late-onset AD (LOAD). T1-weighted MRI scans were obtained at diagnosis and one-year follow-up from 15 EOAD, 10 LOAD, and 38 age-matched controls. Voxel-based and tensor-based morphometry were used, respectively, to assess the baseline and progression of atrophy. At baseline, EOAD patients already showed a widespread atrophy in temporal, parietal, occipital, and frontal cortices. After one year, EOAD had atrophy progression in medial temporal and medial parietal cortices. At baseline, LOAD patients showed atrophy in the medial temporal regions only, and, after one year, an extensive pattern of atrophy progression in the same neocortical cortices of EOAD. Although atrophy mainly involved different lateral neocortical or medial temporal hubs at baseline, it eventually progressed along the same brain default-network regions in both groups. The cortical region showing a significant progression in both groups was the medial precuneus/posterior cingulate.