White and Gray Matter Abnormalities in Manifest Huntington's Disease: Cross-Sectional and Longitudinal Analysis

External evaluation of a deep learning-based approach for automated brain volumetry in patients with huntington's disease

A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for automated volumetry and to compare the results with the manual measurement methods used in clinical practice as well as volume calculations of the caudate nuclei based on manual segmentations. Twenty-two patients were included retrospectively, consisting of eleven patients with Huntington's disease and caudate nucleus atrophy and an age- and sex-matched control group. To quantify caudate head atrophy, the frontal horn width to intercaudate distance ratio and the intercaudate distance to inner table width ratio were obtained. The software mdbrain was used for automated volumetry. Manually measured ratios and automatically measured volumes of the groups were compared using two-sample t-tests. Pearson correlation analyses were performed. The relative difference between automatically and manually determined volumes of the caudate nuclei was calculated. Both ratios were significantly different between the groups. The automatically and manually determined volumes of the caudate nuclei showed a high level of agreement with a mean relative discrepancy of - 2.3 ± 5.5%. The Huntington's disease group showed significantly lower volumes in a variety of supratentorial brain structures. The highest degree of atrophy was shown for the caudate nucleus, putamen, and pallidum (all p < .0001). The caudate nucleus volume and the ratios were found to be strongly correlated in both groups. In conclusion, in patients with progressed Huntington's disease, it was shown that the automatically determined caudate nucleus volume correlates strongly with measured ratios commonly used in clinical practice. Both methods allowed clear differentiation between groups in this collective. The software additionally allows radiologists to more objectively assess the involvement of a variety of brain structures that are less accessible to standard semiquantitative methods.

Deep learning-based grading of white matter hyperintensities enables identification of potential markers in multi-sequence MRI data

BACKGROUND

White matter hyperintensities (WMHs) are widely-seen in the aging population, which are associated with cerebrovascular risk factors and age-related cognitive decline. At present, structural atrophy and functional alterations coexisted with WMHs lacks comprehensive investigation. This study developed a WMHs risk prediction model to evaluate WHMs according to Fazekas scales, and to locate potential regions with high risks across the entire brain.

METHODS

We developed a WMHs risk prediction model, which consisted of the following steps: T2 fluid attenuated inversion recovery (T2-FLAIR) image of each participant was firstly segmented into 1000 tiles with the size of 32 × 32 × 1, features from the tiles were extracted using the ResNet18-based feature extractor, and then a 1D convolutional neural network (CNN) was used to score all tiles based on the extracted features. Finally, a multi-layer perceptron (MLP) was constructed to predict the Fazekas scales based on the tile scores. The proposed model was trained using T2-FLAIR images, we selected tiles with abnormal scores in the test set after prediction, and evaluated their corresponding gray matter (GM) volume, white matter (WM) volume, fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF) via longitudinal and multi-sequence Magnetic Resonance Imaging (MRI) data analysis.

RESULTS

The proposed WMHs risk prediction model could accurately predict the Fazekas ratings based on the tile scores from T2-FLAIR MRI images with accuracy of 0.656, 0.621 in training data set and test set, respectively. The longitudinal MRI validation revealed that most of the high-risk tiles predicted by the WMHs risk prediction model in the baseline images had WMHs in the corresponding positions in the longitudinal images. The validation on multi-sequence MRI demonstrated that WMHs were associated with GM and WM atrophies, WM micro-structural and perfusion alterations in high-risk tiles, and multi-modal MRI measures of most high-risk tiles showed significant associations with Mini Mental State Examination (MMSE) score.

CONCLUSION

Our proposed WMHs risk prediction model can not only accurately evaluate WMH severities according to Fazekas scales, but can also uncover potential markers of WMHs across modalities. The WMHs risk prediction model has the potential to be used for the early detection of WMH-related alterations in the entire brain and WMH-induced cognitive decline.

Early whole-body mutant huntingtin lowering averts changes in proteins and lipids important for synapse function and white matter maintenance in the LacQ140 mouse model

Expansion of a triplet repeat tract in exon 1 of the HTT gene causes Huntington's disease (HD). The mutant HTT protein (mHTT) has numerous aberrant interactions with diverse, pleiomorphic effects. Lowering mHTT is a promising approach to treat HD, but it is unclear when lowering should be initiated, how much is necessary, and what duration should occur to achieve benefits. Furthermore, the effects of mHTT lowering on brain lipids have not been assessed. Using a mHtt-inducible mouse model, we analyzed mHtt lowering initiated at different ages and sustained for different time-periods. mHTT protein in cytoplasmic and synaptic compartments of the striatum was reduced 38-52%; however, there was minimal lowering of mHTT in nuclear and perinuclear regions where aggregates formed at 12 months of age. Total striatal lipids were reduced in 9-month-old LacQ140 mice and preserved by mHtt lowering. Subclasses important for white matter structure and function including ceramide (Cer), sphingomyelin (SM), and monogalactosyldiacylglycerol (MGDG), contributed to the reduction in total lipids. Phosphatidylinositol (PI), phosphatidylserine (PS), and bismethyl phosphatidic acid (BisMePA) were also changed in LacQ140 mice. Levels of all subclasses except ceramide were preserved by mHtt lowering. mRNA expression profiling indicated that a transcriptional mechanism contributes to changes in myelin lipids, and some but not all changes can be prevented by mHtt lowering. Our findings suggest that early and sustained reduction in mHtt can prevent changes in levels of select striatal proteins and most lipids, but a misfolded, degradation-resistant form of mHTT hampers some benefits in the long term.

Early whole-body mutant huntingtin lowering averts changes in proteins and lipids important for synapse function and white matter maintenance in the LacQ140 mouse model

Expansion of a triplet repeat tract in exon1 of the HTT gene causes Huntington's disease (HD). The mutant HTT protein (mHTT) has numerous aberrant interactions with diverse, pleiomorphic effects. No disease modifying treatments exist but lowering mutant huntingtin (mHTT) by gene therapy is a promising approach to treat Huntington's disease (HD). It is not clear when lowering should be initiated, how much lowering is necessary and for what duration lowering should occur to achieve benefits. Furthermore, the effects of mHTT lowering on brain lipids have not been assessed. Using a mHtt-inducible mouse model we analyzed whole body mHtt lowering initiated at different ages and sustained for different time-periods. Subcellular fractionation (density gradient ultracentrifugation), protein chemistry (gel filtration, western blot, and capillary electrophoresis immunoassay), liquid chromatography and mass spectrometry of lipids, and bioinformatic approaches were used to test effects of mHTT transcriptional lowering. mHTT protein in cytoplasmic and synaptic compartments of the caudate putamen, which is most affected in HD, was reduced 38-52%. Little or no lowering of mHTT occurred in nuclear and perinuclear regions where aggregates formed at 12 months of age. mHtt transcript repression partially or fully preserved select striatal proteins (SCN4B, PDE10A). Total lipids in striatum were reduced in LacQ140 mice at 9 months and preserved by early partial mHtt lowering. The reduction in total lipids was due in part to reductions in subclasses of ceramide (Cer), sphingomyelin (SM), and monogalactosyldiacylglycerol (MGDG), which are known to be important for white matter structure and function. Lipid subclasses phosphatidylinositol (PI), phosphatidylserine (PS), and bismethyl phosphatidic acid (BisMePA) were also changed in LacQ140 mice. Levels of all subclasses other than ceramide were preserved by early mHtt lowering. Pathway enrichment analysis of RNAseq data imply a transcriptional mechanism is responsible in part for changes in myelin lipids, and some but not all changes can be rescued by mHTT lowering. Our findings suggest that early and sustained reduction in mHtt can prevent changes in levels of select striatal proteins and most lipids but a misfolded, degradation-resistant form of mHTT hampers some benefits in the long term.

Pain in Huntington's disease and its potential mechanisms

Pain is common and frequent in many neurodegenerative diseases, although it has not received much attention. In Huntington's disease (HD), pain is often ignored and under-researched because attention is more focused on motor and cognitive decline than psychiatric symptoms. In HD progression, pain symptoms are complex and involved in multiple etiologies, particularly mental issues such as apathy, anxiety and irritability. Because of psychiatric issues, HD patients rarely complain of pain, although their bodies show severe pain symptoms, ultimately resulting in insufficient awareness and lack of research. In HD, few studies have focused on pain and pain-related features. A detailed and systemic pain history is crucial to assess and explore pain pathophysiology in HD. This review provides an overview concentrating on pain-related factors in HD, including neuropathology, frequency, features, affecting factors and mechanisms. More attention and studies are still needed in this interesting field in the future.

Application Value of Serum Neurofilament Light Protein for Disease Staging in Huntington's Disease

BACKGROUND

Neurofilament light protein (NfL) has been proven to be a sensitive biomarker for Huntington's disease (HD). However, these studies did not include HD patients at advanced stages or with larger CAG repeats (>50), leading to a knowledge gap of the characteristics of NfL.

METHODS

Serum NfL (sNfL) levels were quantified using an ultrasensitive immunoassay. Participants were assessed by clinical scales and 7.0 T magnetic resonance imaging. Longitudinal samples and clinical data were obtained.

RESULTS

Baseline samples were available from 110 controls, 90 premanifest HD (pre-HD) and 137 HD individuals. We found levels of sNfL significantly increased in HD compared to pre-HD and controls (both P < 0.0001). The increase rates of sNfL were differed by CAG repeat lengths. However, there was no difference in sNfL levels in manifest HD from early to late stages. In addition, sNfL levels were associated with cognitive measures in pre-HD and manifest HD group, respectively. The increased levels of sNfL were also closely related to microstructural changes in white matter. In the longitudinal analysis, baseline sNfL did not correlate with subsequent clinical function decline. Random forest analysis revealed that sNfL had good power for predicting disease onset.

CONCLUSIONS

Although sNfL levels are independent of disease stages in manifest HD, it is still an optimal indicator for predicting disease onset and has potential use as a surrogate biomarker of treatment effect in clinical trials. © 2023 International Parkinson and Movement Disorder Society.

Progressive alterations in white matter microstructure across the timecourse of Huntington's disease

BACKGROUND

Whole-brain longitudinal diffusion studies are crucial to examine changes in structural connectivity in neurodegeneration. Here, we investigated the longitudinal alterations in white matter (WM) microstructure across the timecourse of Huntington's disease (HD).

METHODS

We examined changes in WM microstructure from premanifest to early manifest disease, using data from two cohorts with different disease burden. The TrackOn-HD study included 67 controls, 67 premanifest, and 10 early manifest HD (baseline and 24-month data); the PADDINGTON study included 33 controls and 49 early manifest HD (baseline and 15-month data). Longitudinal changes in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, and radial diffusivity from baseline to last study visit were investigated for each cohort using tract-based spatial statistics. An optimized pipeline was employed to generate participant-specific templates to which diffusion tensor imaging maps were registered and change maps were calculated. We examined longitudinal differences between HD expansion-carriers and controls, and correlations with clinical scores, including the composite UHDRS (cUHDRS).

RESULTS

HD expansion-carriers from TrackOn-HD, with lower disease burden, showed a significant longitudinal decline in FA in the left superior longitudinal fasciculus and an increase in MD across subcortical WM tracts compared to controls, while in manifest HD participants from PADDINGTON, there were significant widespread longitudinal increases in diffusivity compared to controls. Baseline scores in clinical scales including the cUHDRS predicted WM microstructural change in HD expansion-carriers.

CONCLUSION

The present study showed significant longitudinal changes in WM microstructure across the HD timecourse. Changes were evident in larger WM areas and across more metrics as the disease advanced, suggesting a progressive alteration of WM microstructure with disease evolution.

Investigating longitudinal changes to frontal cortico-striatal tracts in Huntington's disease: the IMAGE-HD study

The striatum is the principal site of disease pathology in Huntington's disease and contains neural connections to numerous cortical brain regions. Studies examining abnormalities to neural connections find that white matter integrity is compromised in HD; however, further regional, and longitudinal investigation is required. This paper is the first longitudinal investigation into region-based white-matter integrity changes in Huntington's Disease. The aim of this study was to better understand how disease progression impacts white matter tracts connecting the striatum to the prefrontal and motor cortical regions in HD. We used existing neuroimaging data from IMAGE-HD, comprised of 25 pre-symptomatic, 27 symptomatic, and 25 healthy controls at three separate time points (baseline, 18-months, 30-months). Fractional anisotropy, axial diffusivity and radial diffusivity were derived as measures of white matter microstructure. The anatomical regions of interest were identified using the Desikan-Killiany brain atlas. A Group by Time repeated measures ANCOVA was conducted for each tract of interest and for each measure. We found significantly lower fractional anisotropy and significantly higher radial diffusivity in the symptomatic group, compared to both the pre-symptomatic group and controls (the latter two groups did not differ from each other), in the rostral middle frontal and superior frontal tracts; as well as significantly higher axial diffusivity in the rostral middle tracts only. We did not find a Group by Time interaction for any of the white matter integrity measures. These findings demonstrate that whilst the microstructure of white matter tracts, extending from the striatum to these regions of interest, are compromised during the symptomatic stages of Huntington's disease, 36-month follow-up did not show progressive changes in these measures. Additionally, no correlations were found between clinical measures and tractography changes, indicating further investigations into the relationship between tractography changes and clinical symptoms in Huntington's disease are required.

Fixel-Based Analysis Effectively Identifies White Matter Tract Degeneration in Huntington's Disease

Microstructure damage in white matter might be linked to regional and global atrophy in Huntington's Disease (HD). We hypothesize that degeneration of subcortical regions, including the basal ganglia, is associated with damage of white matter tracts linking these affected regions. We aim to use fixel-based analysis to identify microstructural changes in the white matter tracts. To further assess the associated gray matter damage, diffusion tensor-derived indices were measured from regions of interest located in the basal ganglia. Diffusion weighted images were acquired from 12 patients with HD and 12 healthy unrelated controls using a 3 Tesla scanner. Reductions in fixel-derived metrics occurs in major white matter tracts, noticeably in corpus callosum, internal capsule, and the corticospinal tract, which were closely co-localized with the regions of increased diffusivity in basal ganglia. These changes in diffusion can be attributed to potential axonal degeneration. Fixel-based analysis is effective in studying white matter tractography and fiber changes in HD.

Time will tell: Decision making in premanifest and manifest Huntington's disease

OBJECTIVE

To investigate cognitive flexibility in premanifest and manifest Huntington's disease (HD).

BACKGROUND

HD is an autosomal dominant neurodegenerative disease characterized by motor, cognitive, and behavioral abnormalities with typical motor symptoms. In this study, we wanted to assess decision making in premanifest (pre-HD) and manifest HD patients.

METHODS

A total of 77 non-demented subjects including 29 pre-HD, 22 manifest HD patients, and 26 healthy controls (HC) were included. We stratified the pre-HD group based on their estimated years to disease onset into a far (FAR, n = 13) and a near (NEAR, n = 16) group. Furthermore, participants performed the Montreal cognitive assessment battery (MoCA), the trail making task part A and B (TMT A, TMT B), the Symbol digit modalities test (SDMT), and the beads task.

RESULTS

In the beads task, HD patients gathered less information than all other groups (all p-values < .001). Furthermore, the NEAR group gathered less information than the FAR group (p < .001) and HC (p = .001). There was no difference between the HC and the FAR group (p = 1.0). In the TMT and the SDMT, HD patients were slower than all other groups (all p-values < .01) but there were no other significant differences.

CONCLUSIONS

Decision making with a higher degree of uncertainty may be an early neuropsychological sign to indicate the disease process prior to reaching criteria for motor diagnosis of HD.

Diffusion imaging in Huntington's disease: comprehensive review

Huntington's disease (HD) is a monogenic disorder with 100% penetrance. With the advent of genetic testing in adults, disease-related, structural brain changes can be investigated from the earliest, premorbid stages of HD. While examining macrostructural change characterises global neuronal damage, investigating microstructural alterations provides information regarding brain organisation and its underlying biological properties. Diffusion MRI can be used to track the progression of microstructural anomalies in HD decades prior to clinical disease onset, providing a greater understanding of neurodegeneration. Multiple approaches, including voxelwise, region of interest and tractography, have been used in HD cohorts, showing a centrifugal pattern of white matter (WM) degeneration starting from deep brain areas, which is consistent with neuropathological studies. The corpus callosum, longer WM tracts and areas that are more densely connected, in particular the sensorimotor network, also tend to be affected early during premanifest stages. Recent evidence supports the routine inclusion of diffusion analyses within clinical trials principally as an additional measure to improve understanding of treatment effects, while the advent of novel techniques such as multitissue compartment models and connectomics can help characterise the underpinnings of progressive functional decline in HD.