Health in Aging, Neurodegenerative Diseases and Dementias In Ontario
试验速览
- 阶段
- 不适用
- 状态
- 终止
- 发起方
- 入组人数
- 250
- 试验地点
- 1
- 主要终点
- select subsets of genomic and proteomic features
研究概览
简要总结
The Health in Aging, Neurodegenerative Diseases and DementiaS in ONTario (HANDDS-ONT) Study is an observational study that takes place in the comfort of participant's home, with no study visits occurring in a clinic. The study is recruiting people living with a neurodegenerative disease or the effects of stroke, along with healthy, aging individuals. Studying both groups will help ONDRI researchers to:
- understand how the diseases affect different people
- discover ways to potentially detect diseases earlier
- find ways to help people manage their daily health related behaviours
Participant data is collected virtually through wearables - small sensors worn on the wrist, ankle and chest -- for 7-10 days, as participants go about their daily activities. Data is also collected from questionnaires regarding mood and quality of life. Blood samples will be collected to understand how one's genetic makeup could provide for earlier detection of some conditions, and for analysis of certain risk factors. Combining the information from the sensors (walking patterns, sleep, heart rate/rhythm, etc.), the questionnaires and the blood samples will allow researchers to better understand aging, with and without a neurodegenerative condition, over a period of time.
Participants will receive a personalized health and activity report, describing sleep and activity during the time the wearable sensors were worn. This information may help participants better understand and manage some aspects of their overall health and it can be shared with their circle of care.
详细描述
HANDDS-ONT is designed with the following principal research question in mind:
Can the integration of biosamples, clinical data and remote wearable biosensor data across aging and neurodegenerative disease cohorts i) provide valuable diagnostic data, ii) demonstrate predictive utility for important clinical outcomes and iii) guide daily decisions and care for individuals living with neurodegenerative diseases? Ultimately we aim to improve the lived-experience of individuals affected by dementia. This protocol focuses on building the foundation for this long-term objective by adapting the NIA-AA framework to link genetic, proteomic, and free-living behavioural signatures across NDD cohorts.
Objectives:
Objective 1 will examine the expression of single proteins or sets of proteins (i.e., protein biomarkers), and different gene mutation inheritance patterns (e.g. mutation negative, monogenic mutation, polygenic mutations), to help identify unique cohorts with similar symptoms and free-living behavioural profiles.
Objective 2 will examine the relationship between multidimensional data (genomic-proteomic signatures, functional behaviours extracted from free-living data collected with wearable biosensors), and the risk for adverse health outcomes (e.g., ED visits, hospitalizations, long-term care admission, death, comorbid disease).
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •All Participants:
- •Informed Consent provided by participant or substitute decision maker
- •Age 18 and older
- •Participant must rate his/her level of proficiency speaking and understanding English at 7 out of 10 or higher on the a modified version of the LEAP-Q *
- •Telephone or internet access
- •Ability to attend a LifeLab facility of participant's choice to provide blood sample
- •Under the care of a primary medical care provider (e.g. family physician or nurse practitioner) and/or specialist and their name provided for purposes of reporting incidental findings.
- •Participants must have proficiency in English to understand study instructions and respond to questionnaires licensed for use in English only. Study does not have resources for translation of study documents/certified translators.
- •Participants with Neurodegenerative Diseases:
- •Participant-reported diagnosis of meeting "possible or probable" clinical criteria for AD, MCI, PD, PD+ (e.g. MSA/PSP/CBD/LBD), ALS, FTD or Cerebrovascular disease.
- •Aging adults without a specific diagnosis, but who have cognitive symptoms (Telephone Interview for Cognitive Status-Modified (TICS-M; Total score <32) will be assigned to the MCI cohort.
排除标准
- •Underlying conditions which may interfere with the participant's ability to participate in the study or may compromise study results, including but not limited to:
- •Contraindication to the biosensors as outlined by biosensor manufacturers,
- •Substance abuse within the past year or history of alcohol or drug abuse which the study team feels may interfere with the participant's ability to comply with the study procedures.
- •Known brain tumour (e.g. glioblastoma, metastatic cancer to the brain)
- •Prior brain surgeries that the study team feels will interfere with participation
- •Known history of poor venous access or difficulties with blood draws
- •Significant psychiatric disorders (e.g. untreated major depression, psychosis)
结局指标
主要结局
select subsets of genomic and proteomic features
时间窗: 2 years
. Multiple (mass) univariate tests will be used to rank features and false discovery rate adjustment will be used to establish feature selection threshold. Identification of multivariate associations will be performed by simultaneous models of the independent projections on the multiple genomic-proteomic features with penalized optimization. Multi-class LASSO or sparse LDA will be used to identify features associated with clinical-functional clusters.
identify profiles of clinical and functional expression
时间窗: 2 years
a semi-guided approach will identify multivariate projections using techniques such as PCA and CA from summary measures with prima facie validity of association with cognition (e.g. variability of cardiac RR interval, average total sleep time, first quartile of Fourier transform of acceleration while walking, body mass index, age) extracted from clinical eCRF and biosensor data streams.
Generate behavioural/functional profiles from the wearable biosensors
时间窗: 7-10 day sensor wear period
data collected during the biosensor wear period will be post-processed to extract additional summary measures and patterns of behaviour. Sample measures include: amount of time in sedentary/light/moderate/vigorous intensity activity, total active minutes, estimate of energy expenditure, total walking activity, step count, walking bout durations, characteristics of walking (e.g. cadence, gait velocity, etc.), imbalance and fall events, sleep duration, number of arousals, inter-daily sleep stability, intra-daily sleep variability, sleep fragmentation, heart rate (beats per minute), heart rate variability.
次要结局
未报告次要终点