Periodic Reporting for period 1 - RHYTHM IN DEMENTIA (Circadian rhythm: from preclinical to post-diagnosis dementia)
Periodo di rendicontazione: 2023-05-01 al 2025-10-31
Body functions and biological processes are regulated over the 24-hour day/night period by an internal biological clock; sleep/wake cycle is its most visible manifestation of this bio-behavioural circadian rhythm. Circadian rhythm disruptions have long been observed in patients with dementia and emerging evidence points to their presence in the preclinical period of dementia. This suggests that certain aspects of circadian rhythm could be useful in identification of high-risk individuals and could serve as potential targets for interventions to delay dementia onset and progression. This requires an in-depth understanding of the role of circadian rhythm in dementia pathogenesis. As population ageing increases dementia burden, it is critical to find strategies to identify patients at risk of dementia with precision, prevent, and slow its progression. Building on recent advances in accelerometery (to assess circadian rhythm features comprehensively) and dementia biomarkers (deep-phenotyping of dementia pathogenesis), RHYTHM IN DEMENTIA will make a decisive step-change in knowledge by determining circadian rhythm features involved in dementia processes along the course of the disease. The aims are to: 1) identify core circadian rhythm features that predict 10-year risk of dementia in a community-dwelling cohort of 4000 older adults; 2) uncover specific circadian rhythm disruptions that characterise major dementia subtypes and stages of Alzheimer’s disease (determined by biomarkers) in a new cohort of 1500 patients recruited from two memory clinics in Paris; and 3) ascertain how circadian rhythm affects dementia prognosis in the patient cohort by examining cognitive and functional decline, hospitalisation, institutionalisation, and mortality.
This project will yield new insight into the nature of the association between circadian rhythm and dementia progression. These findings will ultimately inform the potential for a cost-effective and easy to use tool to assess circadian rhythm features to facilitate both identification of patients at risk of dementia and tailored secondary prevention interventions that address circadian rhythm disruptions in dementia patients and slow progression of dementia.
This project will yield new insight into the nature of the association between circadian rhythm and dementia progression. These findings will ultimately inform the potential for a cost-effective and easy to use tool to assess circadian rhythm features to facilitate both identification of patients at risk of dementia and tailored secondary prevention interventions that address circadian rhythm disruptions in dementia patients and slow progression of dementia.
During the initial phase of the RHYTHM IN DEMENTIA project, the main achievements were twofolds.
First, we validated the mathematical properties of rest-activity rhythm accelerometer-derived estimators and implemented these metrics into an open-access R package (https://wadpac.github.io/GGIR/articles/chapter13_CircadianRhythm.html(si apre in una nuova finestra)) to allow their use in other studies. We also found that to have reliable measures of these metrics, 2 to 5 days of accelerometer wear are needed depending on the metric under consideration. This provided information for the next steps for all work packages.
Second, we set up the start of the data collection of a new cohort of patients from 2 memory clinics in Paris, named CIRCAME (https://circame.fr/(si apre in una nuova finestra)) including measures of sociodemographic and behavioural factors, as well as health-related characteristics, a blood test to measure Alzheimer disease and neurodegeneration blood biomarkers, and accelerometer wear for 9 days to measure features of circadian rhythm. The number of patients included at this stage is above 500 and we aim to recruit 800-1000 more patients by the end of December 2026. These data will allow to determine specific circadian rhythm disruptions that characterise major dementia subtypes and stages of Alzheimer’s disease (WP2) and ascertain how circadian rhythm affects dementia prognosis in the patient cohort by examining cognitive and functional decline, hospitalisation, institutionalisation, and mortality (WP3).
In parallel, in WP1, we work on the identification of circadian rhythm profiles using data from 36 metrics of rest-activity rhythm, daytime activity, sleep, and chronotype. In order to validate the method used and the clusters identified, analyses are conducted in parallel in two population-based cohorts of older adults. The next step will be to examine the association of these clusters with subsequent cognitive decline and dementia onset.
We are also working on determining core circadian rhythm features to improve prediction of incident dementia as compared to known risk factors and predictors of dementia. The validity of the identified circadian rhythm risk score will be tested in external study to assess robustness of findings.
First, we validated the mathematical properties of rest-activity rhythm accelerometer-derived estimators and implemented these metrics into an open-access R package (https://wadpac.github.io/GGIR/articles/chapter13_CircadianRhythm.html(si apre in una nuova finestra)) to allow their use in other studies. We also found that to have reliable measures of these metrics, 2 to 5 days of accelerometer wear are needed depending on the metric under consideration. This provided information for the next steps for all work packages.
Second, we set up the start of the data collection of a new cohort of patients from 2 memory clinics in Paris, named CIRCAME (https://circame.fr/(si apre in una nuova finestra)) including measures of sociodemographic and behavioural factors, as well as health-related characteristics, a blood test to measure Alzheimer disease and neurodegeneration blood biomarkers, and accelerometer wear for 9 days to measure features of circadian rhythm. The number of patients included at this stage is above 500 and we aim to recruit 800-1000 more patients by the end of December 2026. These data will allow to determine specific circadian rhythm disruptions that characterise major dementia subtypes and stages of Alzheimer’s disease (WP2) and ascertain how circadian rhythm affects dementia prognosis in the patient cohort by examining cognitive and functional decline, hospitalisation, institutionalisation, and mortality (WP3).
In parallel, in WP1, we work on the identification of circadian rhythm profiles using data from 36 metrics of rest-activity rhythm, daytime activity, sleep, and chronotype. In order to validate the method used and the clusters identified, analyses are conducted in parallel in two population-based cohorts of older adults. The next step will be to examine the association of these clusters with subsequent cognitive decline and dementia onset.
We are also working on determining core circadian rhythm features to improve prediction of incident dementia as compared to known risk factors and predictors of dementia. The validity of the identified circadian rhythm risk score will be tested in external study to assess robustness of findings.