Graph methods to infer spatial disturbances: Application to Huntington's Disease's speech.

OBJECTIVE: Huntington's Disease (HD) is an inherited neurodegenerative disease caused by the mutation of the Htt gene, impacting all aspects of living and functioning. Among cognitive disabilities, spatial capacities are impaired, but their monitoring remains scarce as limited by lengthy experts' assessments. Language offers an alternative medium to evaluate patients' performance in HD. Yet, its capacities to assess HD's spatial abilities are unknown. Here, we aimed to bring proof-of-concept that HD's spatial deficits can be assessed through speech. METHODS: We developed the Spatial Description Model to graphically represent spatial relations described during the Cookie Theft Picture (CTP) task. We increased the sensitivity of our model by using only sentences with spatial terms, unlike previous studies in Alzheimer's disease. 78 carriers of the mutant Htt, including 56 manifest and 22 premanifest individuals, as well as 25 healthy controls were included from the BIOHD & (NCT01412125) & Repair-HD (NCT03119246) cohorts. The convergence and divergence of the model were validated using the SelfCog battery. RESULTS: Our Spatial Description Model was the only one among the four assessed approaches, revealing that individuals with manifest HD expressed fewer spatial relations and engaged in less spatial exploration compared to healthy controls. Their graphs correlated with both visuospatial and language SelfCog performances, but not with motor, executive nor memory functions. CONCLUSIONS: We provide the proof-of-concept using our Spatial Description Model that language can grasp HD patient's spatial disturbances. By adding spatial capabilities to the panel of functions tested by the language, it paves the way for eventual remote clinical application.

Identification of high likelihood of dementia in population-based surveys using unsupervised clustering: a longitudinal analysis.

BACKGROUND: Dementia is defined as a cognitive decline that affects functional status. Longitudinal ageing surveys often lack a clinical diagnosis of dementia though measure cognition and daily function over time. We used unsupervised machine learning and longitudinal data to identify transition to probable dementia. METHODS: Multiple Factor Analysis was applied to longitudinal function and cognitive data of 15,278 baseline participants (aged 50 years and more) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) (waves 1, 2 and 4-7, between 2004 and 2017). Hierarchical Clustering on Principal Components discriminated three clusters at each wave. We estimated probable or "Likely Dementia" prevalence by sex and age, and assessed whether dementia risk factors increased the risk of being assigned probable dementia status using multistate models. Next, we compared the "Likely Dementia" cluster with self-reported dementia status and replicated our findings in the English Longitudinal Study of Ageing (ELSA) cohort (waves 1-9, between 2002 and 2019, 7840 participants at baseline). RESULTS: Our algorithm identified a higher number of probable dementia cases compared with self-reported cases and showed good discriminative power across all waves (AUC ranged from 0.754 [0.722-0.787] to 0.830 [0.800-0.861]). "Likely Dementia" status was more prevalent in older people, displayed a 2:1 female/male ratio, and was associated with nine factors that increased risk of transition to dementia: low education, hearing loss, hypertension, drinking, smoking, depression, social isolation, physical inactivity, diabetes, and obesity. Results were replicated in ELSA cohort with good accuracy. CONCLUSIONS: Machine learning clustering can be used to study dementia determinants and outcomes in longitudinal population ageing surveys in which dementia clinical diagnosis is lacking.

Systematic review of drug therapy for chorea in NXK2-1-related disorders: Efficacy and safety evidence from case studies and series.

BACKGROUND: The NKX2-1-related disorders (NKX2-1-RD) is a rare disorder characterized by choreiform movements along with respiratory and endocrine abnormalities. The European Reference Network of Rare Neurological Disorders funded by the European Commission conducted a systematic review to assess drug treatment of chorea in NKX2-1-RD, aiming to provide clinical recommendations for its management. METHODS: A systematic pairwise review using various databases, including MEDLINE, Embase, Cochrane, CINAHL, and PsycInfo, was conducted. The review included patients diagnosed with chorea and NKX2-1-RD genetic diagnosis, drug therapy as intervention, no comparator, and outcomes of chorea improvement and adverse events. The methodological quality of the studies was assessed, and the study protocol was registered in PROSPERO. RESULTS: Of the 1417 studies examined, 28 studies met the selection criteria, consisting of 68 patients. The studies reported 22 different treatments for chorea, including carbidopa/levodopa, tetrabenazine, clonazepam, methylphenidate, carbamazepine, topiramate, trihexyphenidyl, haloperidol, propranolol, risperidone, and valproate. No clinical improvements were observed with carbidopa/levodopa, tetrabenazine, or clonazepam, and various adverse effects were reported. However, most patients treated with methylphenidate experienced improvements in chorea and reported only a few negative effects. The quality of evidence was determined to be low. CONCLUSIONS: The management of chorea in individuals with NKX2-1-RD presents significant heterogeneity and lack of clarity. While the available evidence suggests that methylphenidate may be effective in improving chorea symptoms, the findings should be interpreted with caution due to the limitations of the studies reviewed. Nonetheless, more rigorous and comprehensive studies are necessary to provide sufficient evidence for clinical recommendations.

Language disorders in patients with striatal lesions: Deciphering the role of the striatum in language performance.

The classical neural model of language refers to a cortical network involving frontal, parietal and temporal regions. However, patients with subcortical lesions of the striatum have language difficulties. We investigated whether the striatum is directly involved in language or whether its role in decision-making has an indirect effect on language performance, by testing carriers of Huntington's disease (HD) mutations and controls. HD is a genetic neurodegenerative disease primarily affecting the striatum and causing language disorders. We asked carriers of the HD mutation in the premanifest (before clinical diagnosis) and early disease stages, and controls to perform two discrimination tasks, one involving linguistic and the other non-linguistic stimuli. We used the hierarchical drift diffusion model (HDDM) to analyze the participants' responses and to assess the decision and non-decision parameters separately. We hypothesized that any language deficits related to decision-making impairments would be reflected in the decision parameters of linguistic and non-linguistic tasks. We also assessed the relative contributions of both HDDM decision and non-decision parameters to the participants' behavioral data (response time and discriminability). Finally, we investigated whether the decision and non-decision parameters of the HDDM were correlated with brain atrophy. The HDDM analysis showed that patients with early HD have impaired decision parameters relative to controls, regardless of the task. In both tasks, decision parameters better explained the variance of response time and discriminability performance than non-decision parameters. In the linguistic task, decision parameters were positively correlated with gray matter volume in the ventral striatum and putamen, whereas non-decision parameters were not. Language impairment in patients with striatal atrophy is better explained by a deficit of decision-making than by a deficit of core linguistic processing. These results suggest that the striatum is involved in language through the modulation of decision-making, presumably by regulating the process of choice between linguistic alternatives.

Identification of High Likelihood of Dementia in Population-Based Surveys using Unsupervised Clustering: a Longitudinal Analysis.

Background: Dementia is defined by cognitive decline that affects functional status. Longitudinal ageing surveys often lack a clinical diagnosis of dementia though measure cognitive and function over time. We used unsupervised machine learning and longitudinal data to identify transition to probable dementia. Methods: Multiple Factor Analysis was applied to longitudinal function and cognitive data of 15,278 baseline participants (aged 50 years and more) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) (waves 1, 2 and 4-7, between 2004 and 2017). Hierarchical Clustering on Principal Components discriminated three clusters at each wave. We estimated probable or "Likely Dementia" prevalence by sex and age, and assessed whether dementia risk factors increased the risk of being assigned probable dementia status using multistate models. Next, we compared the "Likely Dementia" cluster with self-reported dementia status and replicated our findings in the English Longitudinal Study of Ageing (ELSA) cohort (waves 1-9, between 2002 and 2019, 7,840 participants at baseline). Findings: Our algorithm identified a higher number of probable dementia cases compared with self-reported cases and showed good discriminative power across all waves (AUC ranged from 0.754 [0.722-0.787] to 0.830 [0.800-0.861]). "Likely Dementia" status was more prevalent in older people, displayed a 2:1 female/male ratio and was associated with nine factors that increased risk of transition to dementia: low education, hearing loss, hypertension, drinking, smoking, depression, social isolation, physical inactivity, diabetes, and obesity. Results were replicated in ELSA cohort with good accuracy. Interpretation: Machine learning clustering can be used to study dementia determinants and outcomes in longitudinal population ageing surveys in which dementia clinical diagnosis is lacking.

A new approach to digitized cognitive monitoring: validity of the SelfCog in Huntington's disease.

Cognitive deficits represent a hallmark of neurodegenerative diseases, but evaluating their progression is complex. Most current evaluations involve lengthy paper-and-pencil tasks which are subject to learning effects dependent on the mode of response (motor or verbal), the countries' language or the examiners. To address these limitations, we hypothesized that applying neuroscience principles may offer a fruitful alternative. We thus developed the SelfCog, a digitized battery that tests motor, executive, visuospatial, language and memory functions in 15 min. All cognitive functions are tested according to the same paradigm, and a randomization algorithm provides a new test at each assessment with a constant level of difficulty. Here, we assessed its validity, reliability and sensitivity to detect decline in early-stage Huntington's disease in a prospective and international multilingual study (France, the UK and Germany). Fifty-one out of 85 participants with Huntington's disease and 40 of 52 healthy controls included at baseline were followed up for 1 year. Assessments included a comprehensive clinical assessment battery including currently standard cognitive assessments alongside the SelfCog. We estimated associations between each of the clinical assessments and SelfCog using Spearman's correlation and proneness to retest effects and sensitivity to decline through linear mixed models. Longitudinal effect sizes were estimated for each cognitive score. Voxel-based morphometry and tract-based spatial statistics analyses were conducted to assess the consistency between performance on the SelfCog and MRI 3D-T1 and diffusion-weighted imaging in a subgroup that underwent MRI at baseline and after 12 months. The SelfCog detected the decline of patients with Huntington's disease in a 1-year follow-up period with satisfactory psychometric properties. Huntington's disease patients are correctly differentiated from controls. The SelfCog showed larger effect sizes than the classical cognitive assessments. Its scores were associated with grey and white matter damage at baseline and over 1 year. Given its good performance in longitudinal analyses of the Huntington's disease cohort, it should likely become a very useful tool for measuring cognition in Huntington's disease in the future. It highlights the value of moving the field along the neuroscience principles and eventually applying them to the evaluation of all neurodegenerative diseases.

Exploring the values, preferences, and information needs of patients with NKX2-1-related disorders: A qualitative study protocol.

BACKGROUND: NKX2-1-related disorders have a prevalence of 1:500,000 and are therefore considered a rare condition according to the European Commission's definition. The European Reference Network of Rare Neurological Disorders is developing the first clinical practice guideline on the management of this condition, with the support of the Andalusian Health Technology Assessment Area, Endo-ERN, ERN-Lung and Imegen, within the framework of the ERNs Guidelines programme (DG SANTE/2018/B3/030). Within the scope of this programme, it becomes necessary to explore the patient perspective in order to include it in the ongoing clinical practice guideline and accompanying patient information booklet. METHODS AND ANALYSIS: This study will use qualitative methods to explore the values, preferences and information needs of patient with NKX2-1-related disorders and their caregivers. Participants will come from a variety of countries throughout Europe. One focus group and four semi-structured interviews will be conducted. Pairs will analyse the data using Grounded Theory. The Andalusian Regional Ministry of Health's Ethics Coordinating Committee for Biomedical Research (Sevilla, Andalucía, Spain) has approved this study protocol (29/03/2022). DISCUSSION: This is the first study to explore the values, preferences, and information needs of patients with NKX2-1-related disorders. The proposed study's findings will contribute to the generation of useful knowledge that will provide guidance to improve the care given to patients with the studied condition. While this study will provide valuable insights into the perspectives of patients with NKX2-1-related disorders, the findings are unlikely to be generalizable to patients with other conditions.

The striatum in time production: The model of Huntington's disease in longitudinal study.

The unified model of time processing suggests that the striatum is a central structure involved in all tasks that require the processing of temporal durations. Patients with Huntington's disease exhibit striatal degeneration and a deficit in time perception in interval timing tasks (i.e. for duration ranging from hundreds of milliseconds to minutes), but whether this deficit extends to time production remains unclear. In this study, we investigated whether symptomatic patients (HD, N = 101) or presymptomatic gene carriers (Pre-HD, N = 31) of Huntington's disease had a deficit in time production for durations between 4 and 10 s compared to healthy controls and whether this deficit developed over a year for patients. We found a clear deficit in temporal production for HD patients, whereas Pre-HD performed similarly to Controls. For HD patients and Pre-HD participants, task performance was correlated with grey matter volume in the amygdala and caudate, bilaterally. These results confirm that the striatum is involved in interval timing not only in perception but also in production, in accordance with the unified model of time processing. Furthermore, exploratory factor analyses on our data indicated that temporal production was associated with clinical assessments of psychomotor and executive functions. Finally, when retested twelve months later, the deficit of HD patients remained stable, although striatal degeneration was more pronounced. Thus, the simple, short and language-independent temporal production task may be a useful clinical tool to detect striatal degeneration in patients in early stages of Huntington's disease. However, its usefulness to detect presymptomatic stages or for monitoring the evolution of HD over a year seems limited.

Informal care in Huntington's disease: Assessment of objective-subjective burden and its associated risk and protective factors.

BACKGROUND: Because of the genetic transmission of Huntington's disease (HD), informal caregivers (ICs, i.e., non-professional caregivers) might experience consecutive and/or concurrent caregiving roles to support several symptomatic relatives with HD over their life. Additionally, some ICs might be HD carriers. However, whether family burden of care is associated with specific factors in HD remains poorly studied. OBJECTIVE: To provide a quantitative view of the IC burden and identify associated factors. METHODS: This was a cross-sectional assessment of home-dwelling symptomatic HD individuals (from REGISTRY and Bio-HD studies) and their primary adult ICs, including the HD individual's motor, cognitive, behavioral, functional Unified Huntington's Disease Rating Scale score; IC objective burden (quantification of IC time in activities of daily living, instrumental activities of daily living and supervision, using the Resource Utilization in Dementia instrument), IC subjective burden (Zarit Burden Inventory), and ICs' social economic functioning and use of professional home care. RESULTS: We included 80 ICs (mean [SD] age 57 [12.9] years, 60% women) in charge of 80 individuals with early to advanced stage HD (mean age 56 [12.6] years, 51% men). The mean hours of informal care time was high: 7.3 (7.9) h/day (range 0-24); the mean professional home care was 2.8 (2.8) h/day (range 0.1-12.3). This objective burden increased with higher functional loss of the HD individual and with more severe cognitive-behavioral disorders. The mean subjective burden (35.4 [17.8], range 4-73) showed a high level since the earliest stage of HD; it was associated with HD duration (mean 9.2 [4.7] years) and with aggressive symptoms in individuals (44% of cases). The burden was partially related to the multiplex caregiving status (19%). Protective factors lowering the IC burden included the absence of financial hardship (57%), a strong social network (16%) and keeping active on the job market outside home (46%). CONCLUSIONS: The objective-subjective burden of ICs related to changing patterns of neuro-psychiatric symptoms and mitigating environmental characteristics around the HD individual-caregiver dyads.

Cognitive processes of apathy in Huntington's disease show high sensitivity to disease progression.

Background: Disease-modifying treatments for Huntington's disease (HD) are entering clinical trials: there is a pressing need for objective outcome measures of disease progression. Our previous work showed an association between 2 novel, objective cognitive tasks and apathy - a core feature of disease progression in HD. Objective: Evaluate the longitudinal validity and sensitivity of the novel Persistence and Maze tasks to assess their utility as clinical outcome measures in HD. Methods: 83 participants positive for the HD gene and 54 controls performed a battery of established and novel tools, at baseline and 12 month follow up. Results: The Maze task was found to be the most sensitive measure of change at 12 months, including the current gold-standard measure (the composite disease progression score). Conclusion: The Maze task has potential as a novel outcome measure of disease progression in HD and may have utility in other major neurodegenerative diseases.

Annonaceae Consumption Worsens Disease Severity and Cognitive Deficits in Degenerative Parkinsonism.

BACKGROUND: High consumption of Annona muricata fruit has been previously identified as a risk factor for atypical parkinsonism in the French Caribbean islands. OBJECTIVE: We tested whether consumption of Annonaceae products could worsen the clinical phenotype of patients with any form of degenerative parkinsonism. METHODS: We analyzed neurological data from 180 Caribbean parkinsonian patients and specifically looked for dose effects of lifelong, cumulative Annonaceae consumption on cognitive performance. Using unsupervised clustering, we identified one cluster with mild/moderate symptoms (N = 102) and one with severe symptoms including cognitive impairment (N = 78). RESULTS: We showed that even low cumulative consumption of fruits/juices (>0.2 fruit-years) or any consumption of herbal tea from Annonaceae worsen disease severity and cognitive deficits in degenerative parkinsonism including Parkinson's disease (OR fruits-juices: 3.76 [95% CI: 1.13-15.18]; OR herbal tea: 2.91 [95% CI: 1.34-6.56]). CONCLUSION: We suggest that more restrictive public health preventive recommendations should be made regarding the consumption of Annonaceae products. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The burden of Huntington's disease: A prospective longitudinal study of patient/caregiver pairs.

BACKGROUND: Caregiver burden is widely recognized in Huntington's disease, but little is known about the factors determining its evolution over time in the absence of longitudinal studies. Our objective was to identify typical patterns of caregiver burden level and evolution using both patients' and caregivers' characteristics over a one-year period to identify potential levers for alleviation. METHODS: We conducted a prospective multicenter longitudinal study in caregiver/patient pairs in Huntington's disease (NCT02876445) between March 2011 and May 2015. Caregiver data were derived from two questionnaires at one-year interval on perceived burden (Zarit Burden Interview), social environment and support. Caregiver data were linked to clinical and demographic data from patients included in the Biomarker study (NCT01590589). Unsupervised clustering analysis was performed using self-organizing maps. RESULTS: 105 caregiver/patient pairs were included in the analysis. We identified four clusters. Of the two clusters of patients with advanced disease, cluster A was characterized by high levels of irritability and obsessive-compulsive behaviors, with high and increasing burden (N = 30; 29%), cluster B, the more apathetic group, with low and decreasing burden (N = 22; 21%). Clusters C (N = 27; 26%) and D (N = 26; 25%) were composed of patients in earlier stages, associated with a stable burden in group C but a notably increasing one in group D driven by patients' depression scores increase. CONCLUSIONS: Our results revealed the dynamics of caregiver burden over time in Huntington's disease, combining the stage of the disease, the severity of the patients' decline, psychiatric and behavioral disorders, and their evolution over time.

Emotion expression through spoken language in Huntington disease.

Patients with Huntington's disease suffer from disturbances in the perception of emotions; they do not correctly read the body, vocal and facial expressions of others. With regard to the expression of emotions, it has been shown that they are impaired in expressing emotions through face but up until now, little research has been conducted about their ability to express emotions through spoken language. To better understand emotion production in both voice and language in Huntington's Disease (HD), we tested 115 individuals: 68 patients (HD), 22 participants carrying the mutant HD gene without any motor symptoms (pre-manifest HD), and 25 controls in a single-centre prospective observational follow-up study. Participants were recorded in interviews in which they were asked to recall sad, angry, happy, and neutral stories. Emotion expression through voice and language was investigated by comparing the identifiability of emotions expressed by controls, preHD and HD patients in these interviews. To assess separately vocal and linguistic expression of emotions in a blind design, we used machine learning models instead of a human jury performing a forced-choice recognition test. Results from this study showed that patients with HD had difficulty expressing emotions through both voice and language compared to preHD participants and controls, who behaved similarly and above chance. In addition, we did not find any differences in expression of emotions between preHD and healthy controls. We further validated our newly proposed methodology with a human jury on the speech produced by the controls. These results are consistent with the hypothesis that emotional deficits in HD are caused by impaired sensori-motor representations of emotions, in line with embodied cognition theories. This study also shows how machine learning models can be leveraged to assess emotion expression in a blind and reproducible way.

Predicting clinical scores in Huntington's disease: a lightweight speech test.

OBJECTIVES: Using brief samples of speech recordings, we aimed at predicting, through machine learning, the clinical performance in Huntington's Disease (HD), an inherited Neurodegenerative disease (NDD). METHODS: We collected and analyzed 126 samples of audio recordings of both forward and backward counting from 103 Huntington's disease gene carriers [87 manifest and 16 premanifest; mean age 50.6 (SD 11.2), range (27-88) years] from three multicenter prospective studies in France and Belgium (MIG-HD (ClinicalTrials.gov NCT00190450); BIO-HD (ClinicalTrials.gov NCT00190450) and Repair-HD (ClinicalTrials.gov NCT00190450). We pre-registered all of our methods before running any analyses, in order to avoid inflated results. We automatically extracted 60 speech features from blindly annotated samples. We used machine learning models to combine multiple speech features in order to make predictions at individual levels of the clinical markers. We trained machine learning models on 86% of the samples, the remaining 14% constituted the independent test set. We combined speech features with demographics variables (age, sex, CAG repeats, and burden score) to predict cognitive, motor, and functional scores of the Unified Huntington's disease rating scale. We provided correlation between speech variables and striatal volumes. RESULTS: Speech features combined with demographics allowed the prediction of the individual cognitive, motor, and functional scores with a relative error from 12.7 to 20.0% which is better than predictions using demographics and genetic information. Both mean and standard deviation of pause durations during backward recitation and clinical scores correlated with striatal atrophy (Spearman 0.6 and 0.5-0.6, respectively). INTERPRETATION: Brief and examiner-free speech recording and analysis may become in the future an efficient method for remote evaluation of the individual condition in HD and likely in other NDD.

Corrigendum: Combining Literature Review With a Ground Truth Approach for Diagnosing Huntington's Disease Phenocopy.

[This corrects the article DOI: 10.3389/fneur.2022.817753.].

Self-Reported Social Relationship Capacities Predict Motor, Functional and Cognitive Decline in Huntington's Disease.

Huntington's Disease (HD) is an inherited neurodegenerative disease characterized by a combination of motor, cognitive, and behavioral disorders. The social and behavioral symptoms observed in HD patients impact their quality of life and probably explain their relational difficulties, conflicts, and social withdrawal. In this study, we described the development of the Social Relationship Self-Questionnaire (SRSQ), a self-reporting questionnaire that assesses how HD patients perceived their social relationships. The scale was proposed for 66 HD patients at an early stage of the disease, 32 PreHD patients (individuals carrying the mutant gene without motor symptoms), and 66 controls. The HD patients were included in a prospective longitudinal follow-up for an average of 1.07 years with motor, functional, cognitive, and behavioral assessments. Based on the HD patients' answers at baseline, we identified two domains in the SRSQ. The first domain was related to social motivation and correlated with cognitive performance. The second domain was related to emotional insight and correlated with behavioral symptoms such as apathy, anxiety, and irritability. We discovered that both SRSQ domain scores at baseline predicted future motor, functional, and cognitive decline in HD.

Combining Literature Review With a Ground Truth Approach for Diagnosing Huntington's Disease Phenocopy.

One percent of patients with a Huntington's disease (HD) phenotype do not have the Huntington (HTT) gene mutation. These are known as HD phenocopies. Their diagnosis is still a challenge. Our objective is to provide a diagnostic approach to HD phenocopies based on medical expertise and a review of the literature. We employed two complementary approaches sequentially: a review of the literature and two surveys analyzing the daily clinical practice of physicians who are experts in movement disorders. The review of the literature was conducted from 1993 to 2020, by extracting articles about chorea or HD-like disorders from the database Pubmed, yielding 51 articles, and analyzing 20 articles in depth to establish the surveys. Twenty-eight physicians responded to the first survey exploring the red flags suggestive of specific disease entities. Thirty-three physicians completed the second survey which asked for the classification of paraclinical tests according to their diagnostic significance. The analysis of the results of the second survey used four different clustering algorithms and the density-based clustering algorithm DBSCAN to classify the paraclinical tests into 1st, 2nd, and 3rd-line recommendations. In addition, we included suggestions from members of the European Reference Network-Rare Neurological Diseases (ERN-RND Chorea & Huntington disease group). Finally, we propose guidance that integrate the detection of clinical red flags with a classification of paraclinical testing options to improve the diagnosis of HD phenocopies.