Neuropsychology and Vascular Cognitive Impairment and Dementia.

Neuropsychology is an integral component of health care assessment for persons with vascular contributions to cognitive impairment and dementia. Since syndromes of vascular cognitive decline have multiple and varying pathophysiologies, anatomic brain locations, and levels of severity, neuropsychological assessment can be critical to clarify the cognitive manifestations of the disease, potential consequences for the patient and family, as well as the prognosis for future life planning. Cognitive profiles of vascular cognitive declines and relevant neuropsychological literature are reviewed here to provide the practicing physician with guidance for best clinical care practices.

Prognostic enrichment for early-stage Huntington's disease: An explainable machine learning approach for clinical trial.

BACKGROUND: In Huntington's disease clinical trials, recruitment and stratification approaches primarily rely on genetic load, cognitive and motor assessment scores. They focus less on in vivo brain imaging markers, which reflect neuropathology well before clinical diagnosis. Machine learning methods offer a degree of sophistication which could significantly improve prognosis and stratification by leveraging multimodal biomarkers from large datasets. Such models specifically tailored to HD gene expansion carriers could further enhance the efficacy of the stratification process. OBJECTIVES: To improve stratification of Huntington's disease individuals for clinical trials. METHODS: We used data from 451 gene positive individuals with Huntington's disease (both premanifest and diagnosed) from previously published cohorts (PREDICT, TRACK, TrackON, and IMAGE). We applied whole-brain parcellation to longitudinal brain scans and measured the rate of lateral ventricular enlargement, over 3 years, which was used as the target variable for our prognostic random forest regression models. The models were trained on various combinations of features at baseline, including genetic load, cognitive and motor assessment score biomarkers, as well as brain imaging-derived features. Furthermore, a simplified stratification model was developed to classify individuals into two homogenous groups (low risk and high risk) based on their anticipated rate of ventricular enlargement. RESULTS: The predictive accuracy of the prognostic models substantially improved by integrating brain imaging features alongside genetic load, cognitive and motor biomarkers: a 24 % reduction in the cross-validated mean absolute error, yielding an error of 530 mm3/year. The stratification model had a cross-validated accuracy of 81 % in differentiating between moderate and fast progressors (precision = 83 %, recall = 80 %). CONCLUSIONS: This study validated the effectiveness of machine learning in differentiating between low- and high-risk individuals based on the rate of ventricular enlargement. The models were exclusively trained using features from HD individuals, which offers a more disease-specific, simplified, and accurate approach for prognostic enrichment compared to relying on features extracted from healthy control groups, as done in previous studies. The proposed method has the potential to enhance clinical utility by: i) enabling more targeted recruitment of individuals for clinical trials, ii) improving post-hoc evaluation of individuals, and iii) ultimately leading to better outcomes for individuals through personalized treatment selection.

Genetic modifiers of somatic expansion and clinical phenotypes in Huntington's disease reveal shared and tissue-specific effects.

Huntington's disease (HD), due to expansion of a CAG repeat in HTT , is representative of a growing number of disorders involving somatically unstable short tandem repeats. We find that overlapping and distinct genetic modifiers of clinical landmarks and somatic expansion in blood DNA reveal an underlying complexity and cell-type specificity to the mismatch repair-related processes that influence disease timing. Differential capture of non-DNA-repair gene modifiers by multiple measures of cognitive and motor dysfunction argues additionally for cell-type specificity of pathogenic processes. Beyond trans modifiers, differential effects are also illustrated at HTT by a 5'-UTR variant that promotes somatic expansion in blood without influencing clinical HD, while, even after correcting for uninterrupted CAG length, a synonymous sequence change at the end of the CAG repeat dramatically hastens onset of motor signs without increasing somatic expansion. Our findings are directly relevant to therapeutic suppression of somatic expansion in HD and related disorders and provide a route to define the individual neuronal cell types that contribute to different HD clinical phenotypes.

Longitudinal imaging highlights preferential basal ganglia circuit atrophy in Huntington's disease.

Huntington's disease is caused by a CAG repeat expansion in the Huntingtin gene (HTT), coding for polyglutamine in the Huntingtin protein, with longer CAG repeats causing earlier age of onset. The variable 'Age' × ('CAG'-L), where 'Age' is the current age of the individual, 'CAG' is the repeat length and L is a constant (reflecting an approximation of the threshold), termed the 'CAG Age Product' (CAP) enables the consideration of many individuals with different CAG repeat expansions at the same time for analysis of any variable and graphing using the CAG Age Product score as the X axis. Structural MRI studies have showed that progressive striatal atrophy begins many years prior to the onset of diagnosable motor Huntington's disease, confirmed by longitudinal multicentre studies on three continents, including PREDICT-HD, TRACK-HD and IMAGE-HD. However, previous studies have not clarified the relationship between striatal atrophy, atrophy of other basal ganglia structures, and atrophy of other brain regions. The present study has analysed all three longitudinal datasets together using a single image segmentation algorithm and combining data from a large number of subjects across a range of CAG Age Product score. In addition, we have used a strategy of normalizing regional atrophy to atrophy of the whole brain, in order to determine which regions may undergo preferential degeneration. This made possible the detailed characterization of regional brain atrophy in relation to CAG Age Product score. There is dramatic selective atrophy of regions involved in the basal ganglia circuit-caudate, putamen, nucleus accumbens, globus pallidus and substantia nigra. Most other regions of the brain appear to have slower but steady degeneration. These results support (but certainly do not prove) the hypothesis of circuit-based spread of pathology in Huntington's disease, possibly due to spread of mutant Htt protein, though other connection-based mechanisms are possible. Therapeutic targets related to prion-like spread of pathology or other mechanisms may be suggested. In addition, they have implications for current neurosurgical therapeutic approaches, since delivery of therapeutic agents solely to the caudate and putamen may miss other structures affected early, such as nucleus accumbens and output nuclei of the striatum, the substantia nigra and the globus pallidus.

The temporal event-based model: Learning event timelines in progressive diseases.

Timelines of events, such as symptom appearance or a change in biomarker value, provide powerful signatures that characterise progressive diseases. Understanding and predicting the timing of events is important for clinical trials targeting individuals early in the disease course when putative treatments are likely to have the strongest effect. However, previous models of disease progression cannot estimate the time between events and provide only an ordering in which they change. Here, we introduce the temporal event-based model (TEBM), a new probabilistic model for inferring timelines of biomarker events from sparse and irregularly sampled datasets. We demonstrate the power of the TEBM in two neurodegenerative conditions: Alzheimer's disease (AD) and Huntington's disease (HD). In both diseases, the TEBM not only recapitulates current understanding of event orderings but also provides unique new ranges of timescales between consecutive events. We reproduce and validate these findings using external datasets in both diseases. We also demonstrate that the TEBM improves over current models; provides unique stratification capabilities; and enriches simulated clinical trials to achieve a power of 80% with less than half the cohort size compared with random selection. The application of the TEBM naturally extends to a wide range of progressive conditions.

Factors Associated With the Place of Death in Huntington Disease: Analysis of Enroll-HD.

Background: Most people prefer to die at home. Hospice is the standard in end-of-life care for people with Huntington disease (HD), a neurodegenerative genetic disorder that affects people in middle adulthood. Yet, we have little knowledge regarding the place of death for people with HD. Therefore, the current state of knowledge limits HD clinicians' ability to conduct high-quality goals of care conversations. Objectives: We sought to determine the factors associated with the place of death in people with HD. Design: We obtained cross-sectional data from Enroll-HD and included participants with a positive HD mutation of 36 or more CAG repeats. Results: Out of 16,120 participants in the Enroll-HD study, 536 were reported as deceased. The mean age at death was 60. The leading place of death was home (29%), followed by the hospital (23%). The adjusted odds ratio (aOR) of dying at a skilled nursing facility was significantly lower for those partnered (aOR: 0.48, confidence interval [95% CI]: 0.26-0.86). The aOR for dying on hospice compared to home was increased in a person with some college and above (aOR: 2.40, 95% CI: 1.21-4.75). Conclusions: Our data further suggest that models that predict the place of death for serious illnesses do not appear to generalize to HD. The distribution in the places of death within HD was not uniform. Our findings may assist HD clinicians in communication during goals of care conversations.

Death Anxiety in Huntington Disease: Longitudinal Heath-Related Quality-of-Life Outcomes.

Objective: Death anxiety, represented by the HDQLIFE™ Concern with Death and Dying (CwDD) patient-reported outcome (PRO) questionnaire, captures a person's worry about the death and dying process. Previous work suggests that death anxiety remains an unremitting burden throughout all stages of Huntington disease (HD). Although palliative interventions have lessened death anxiety among people with advanced cancer, none has yet to undergo testing in the HD population. An account of how death anxiety is associated with longitudinal changes to aspects of health-related quality of life (HRQoL) would help optimize neuropalliative interventions for people with HD. Methods: HDQLIFE collected PROs concerning physical, mental, social, and cognitive HRQoL domains and clinician-rated assessments from people with HD at baseline and 12 and 24 months. Linear mixed-effects models were created to determine how baseline death anxiety was associated with follow-up changes in HRQoL PROs after controlling for baseline death anxiety and other disease and sociodemographic covariates. Results: Higher baseline HDQLIFE CwDD is associated with 12- and 24-month declines in HDQLIFE Speech Difficulties, neurology quality of life (NeuroQoL) Depression, Suicidality, HDQLIFE Meaning and Purpose, and NeuroQoL Positive Affect and Well-being. Interpretation: Death anxiety may be a risk factor for worsening mental health and speech difficulty. A further prospective study is required to evaluate whether interventions on death anxiety or mental health generally can reduce declines in HRQoL for people with HD over time.

Comprehensive shape analysis of the cortex in Huntington's disease.

The striatum has traditionally been the focus of Huntington's disease research due to the primary insult to this region and its central role in motor symptoms. Beyond the striatum, evidence of cortical alterations caused by Huntington's disease has surfaced. However, findings are not coherent between studies which have used cortical thickness for Huntington's disease since it is the well-established cortical metric of interest in other diseases. In this study, we propose a more comprehensive approach to cortical morphology in Huntington's disease using cortical thickness, sulcal depth, and local gyrification index. Our results show consistency with prior findings in cortical thickness, including its limitations. Our comparison between cortical thickness and local gyrification index underscores the complementary nature of these two measures-cortical thickness detects changes in the sensorimotor and posterior areas while local gyrification index identifies insular differences. Since local gyrification index and cortical thickness measures detect changes in different regions, the two used in tandem could provide a clinically relevant measure of disease progression. Our findings suggest that differences in insular regions may correspond to earlier neurodegeneration and may provide a complementary cortical measure for detection of subtle early cortical changes due to Huntington's disease.

Vascular contributions to Alzheimer's disease.

Alzheimer's disease (AD) is the most common cause of dementia and is characterized by progressive neurodegeneration and cognitive decline. Understanding the pathophysiology underlying AD is paramount for the management of individuals at risk of and suffering from AD. The vascular hypothesis stipulates a relationship between cardiovascular disease and AD-related changes although the nature of this relationship remains unknown. In this review, we discuss several potential pathological pathways of vascular involvement in AD that have been described including dysregulation of neurovascular coupling, disruption of the blood brain barrier, and reduced clearance of metabolite waste such as beta-amyloid, a toxic peptide considered the hallmark of AD. We will also discuss the two-hit hypothesis which proposes a 2-step positive feedback loop in which microvascular insults precede the accumulation of Aß and are thought to be at the origin of the disease development. At neuroimaging, signs of vascular dysfunction such as chronic cerebral hypoperfusion have been demonstrated, appearing early in AD, even before cognitive decline and alteration of traditional biomarkers. Cerebral small vessel disease such as cerebral amyloid angiopathy, characterized by the aggregation of Aß in the vessel wall, is highly prevalent in vascular dementia and AD patients. Current data is unclear whether cardiovascular disease causes, precipitates, amplifies, precedes, or simply coincides with AD. Targeted imaging tools to quantitatively evaluate the intracranial vasculature and longitudinal studies in individuals at risk for or in the early stages of the AD continuum could be critical in disentangling this complex relationship between vascular disease and AD.