EpiAgeing

/EpiAgeing
EpiAgeing 2018-02-06T13:14:03+00:00

Epidemiology of Ageing & Neurodegenerative diseases

The team is composed of epidemiologists, a neuro-epidemiologist, and statisticians. We work in close collaboration with the Whitehall study.

Main characteristics of our approach to research on ageing: study of functional status as well as neurodegenerative diseases, consideration of both cognitive & motor change in order to assess how central nervous system dysfunction impacts the sequence of age-related changes, repeat assessment of multiple risk factors (social, behavioural, cardiometabolic, inflammatory, etc.), strong methodological core in order to tackle limitations due to suboptimal consideration of missing data, competing risks, selection, & reverse causation biases.

EpiAgeing team will join the Centre in 2019.

  • Determinants of heterogeneity in cognitive & motor decline with a focus on understanding changes over the adult lifecourse using social, behavioural, and biological risk factors.

  • Alzheimer’s disease (AD) for the role of imaging cerebrospinal fluid biomarkers in patients referred to memory clinics, using data from multiple centres in France and other European countries.

  • Dementia, aetiological research that takes the decades-long latent phase of dementia into account. A range of risk factors have been assessed repeatedly, starting at age 35, in order to allow the identification of modifiable risk factors for dementia.

  • Multimorbidity to address shortcomings in the research on multimorbidity by use of objective rather than self-reported chronic conditions, longitudinal design, and assessment of how multimorbidity affects the prognosis of neurodegenerative diseases.

Information

  • Pr. Archana Singh-Manoux
    Director of the team
    archana.singh-manoux@inserm.fr

Major projects

Whitehall Study

Development of a multi-factorial risk profile for dementia in the Whitehall Study

Much of the research on dementia focusses on single risk factors, adjusting out the effects of other risk factors without accounting for their co-existence. The objective of this project is to develop a multi-factorial risk profile for dementia, using risk factors assessed in midlife. Risk profiles combine multiple predictors by assigning relative weights to each predictor to estimate personalized risk for each individual.

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Accelerometers in population studies

Wearable devices such as accelerometers provide moment-by-moment quantification of physical activity, sedentary behaviour and sleep patterns. These assessments are objective and comprehensive, in that assessments are not restricted to a set of predefined measures so that health correlates of behaviour patterns can be studies in greater depth. We used a wrist-worn accelerometer (GeneActiv, tri-axial signals over 9 full 24-hour days) on over 4000 persons; the data extraction algorithm (package R) has been made available to the scientific community.

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MemScreen

Development and validation of a smartphone application aimed at general practitioners for detecting amnestic cognitive impairment in patients with a memory complaint. Data collection on the French version of the application is complete, the English version of the application is currently being prepared for validation.

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Multimorbidity: lifecourse approach

Using a longitudinal approach this project aims to determine how clinical, behavioural, and socioeconomic risk factors shape the chronic disease trajectory – from first disease to multimorbidity and subsequent mortality.

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10 Key Publications
  • Sabia S, Dugravot A, Dartigues JF, Abell J, Elbaz A, Kivimäki M, Singh-Manoux A. Physical activity, cognitive decline, and risk of dementia: 28 year follow-up of Whitehall II cohort study.
    BMJ. 2017; 357: j2709.

  • Singh-Manoux A, Dugravot A, Shipley M, Brunner EJ, Elbaz A, Sabia S, Kivimaki M. Obesity trajectories and risk of dementia: 28 years of follow-up in the Whitehall II Study.
    Alzheimers Dement. 2017. pii: S1552-5260(17)33689-0.

  • Dumurgier J, Hanseeuw BJ, Hatling FB, Judge KA, Schultz AP, Chhatwal JP, Blacker D, Sperling RA, Johnson KA, Hyman BT, Gómez-Isla T. Alzheimer’s Disease Biomarkers and Future Decline in Cognitive Normal Older Adults.
    J Alzheimers Dis. 2017; 60(4): 1451-1459.

  • Singh-Manoux A, Fayosse A, Sabia S, Canonico M, Bobak M, Elbaz A, Kivimäki M, Dugravot A. Atrial fibrillation as a risk factor for cognitive decline and dementia.
    Eur Heart J. 2017; 38(34): 2612-2618.

  • Rusmaully J, Dugravot A, Moatti JP, Marmot MG, Elbaz A, Kivimaki M, Sabia S, Singh-Manoux A. Contribution of cognitive performance and cognitive decline to associations between socioeconomic factors and dementia: A cohort study.
    PLoS Med. 2017; 14(6): e1002334.

  • Tuligenga RH, Dugravot A, Tabák AG, Elbaz A, Brunner EJ, Kivimäki M, Singh-Manoux A. Midlife type 2 diabetes and poor glycaemic control as risk factors for cognitive decline in early old age: a post-hoc analysis of the Whitehall II cohort study.
    Lancet Diabetes Endocrinol. 2014; 2(3): 228-35.

  • Kaffashian S, Dugravot A, Brunner EJ, Sabia S, Ankri J, Kivimäki M, Singh-Manoux A. Midlife stroke risk and cognitive decline: a 10-year follow-up of the Whitehall II cohort study.
    Alzheimers Dement. 2013; 9(5): 572-9.

  • Sabia S, Elbaz A, Dugravot A, Head J, Shipley M, Hagger-Johnson G, Kivimaki M, Singh-Manoux A. Impact of smoking on cognitive decline in early old age: the Whitehall II cohort study.
    Arch Gen Psychiatry. 2012; 69(6): 627-35.

  • Dumurgier J, Vercruysse O, Paquet C, Bombois S, Chaulet C, Laplanche JL, Peoc’h K, Schraen S, Pasquier F, Touchon J, Hugon J, Lehmann S, Gabelle A. Intersite variability of CSF Alzheimer’s disease biomarkers in clinical setting.
    Alzheimers Dement. 2013; 9(4): 406-13.

  • Singh-Manoux A, Kivimaki M, Glymour MM, Elbaz A, Berr C, Ebmeier KP, Ferrie JE, Dugravot A Timing of onset of cognitive decline: results from Whitehall II prospective cohort study.
    BMJ 2012; 344: d7622.