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OBJECTIVE: Huntington's disease (HD) is a neurodegenerative disorder characterized by progressive motor, cognitive, and psychiatric symptoms. Our aim here was to identify factors that can be modified to slow disease progression even before the first symptoms appear. METHODS: We included 2636 presymptomatic individuals (comparison with family controls) drawn from the prospective observational cohort Enroll-HD, with more than 35 CAG repeats and at least two assessments of disease progression measured with the composite Huntington's disease rating Scale (cUHDRS). The association between sociodemographic factors, health behaviors, health history, and cUHDRS trajectory was assessed with a mixed-effects random forest using partial dependence plots and Shapley additive explanation method. RESULTS: Participants were followed by an average of 3.4 (SD = 1.97) years. We confirmed the negative impact of age and a high number of CAG repeats. We found that a high level of education, a body mass index (BMI) <23 kg/m2 before the age of 40 and >23 kg/m2 thereafter, alcohol consumption of <15 units per week, current coffee consumption and no smoking were linked to slow disease progression, as did no previous exposure to antidepressants or anxiolytic, no psychiatric history or comorbidities, and being female. Other comorbidities or marital status showed no major association with HD evolution. INTERPRETATION: Reducing modifiable risk factors for HD is one way to support the presymptomatic population. A high level of education, low-to-moderate alcohol consumption, no smoking, and BMI control are likely to slow disease progression in this population.
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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.
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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.
