B2982 - Lifecourse aetiology of dementia and cognitive decline Improving causal inference - 13/11/2017

B number: 
B2982
Principal applicant name: 
Emma Louise Anderson | MRC Integrative Epidemiology Unit
Co-applicants: 
Title of project: 
Lifecourse aetiology of dementia and cognitive decline: Improving causal inference.
Proposal summary: 

Dementia describes a set of symptoms including memory loss and difficulties with thinking, problem-solving or language. The term 'dementia' encompasses several different types of disease, with Alzheimer's dementia being the most common. Dementia is now the second leading cause of death in England and Wales, thus, finding ways to prevent dementia is a public health priority. Dementia is not only a great burden on our economy and health care system, but also on the families and friends of those suffering with the disease. Furthermore, medications that are currently available are unable to delay the onset of, or cure, dementia. It is therefore essential that we identify factors that increase a person's risk of getting dementia, especially things that we are able to change (such as smoking or diet), so that we can intervene and try to prevent it occurring in the first place.

Findings from existing studies that have tried to identify risk factors for dementia are conflicting. The only risk factors for which we have good, consistent evidence so far are age (the older a person is, the greater their risk of dementia), sex (being female), low education, head trauma and some cardiovascular risk factors such as diabetes. Evidence for other risk factors such as smoking, alcohol consumption, diet and physical activity, is less clear in that they have reported positive (i.e. increasing risk), negative (i.e. decreasing risk) and no effects on dementia. One key problem is that there are many complications when studying causes of dementia. It is a complex disease that can begin up to 20 years before people start presenting with symptoms, making it difficult to assess whether the risk factors being studied are a cause or a consequence of dementia. For example, it is still unclear whether depression in adulthood is a risk factor for dementia, or whether the early brain changes in dementia cases result in depressive symptoms. Moreover, people with dementia who are still actively participating in studies are often the more 'healthy' than those who leave the study due to illness or death, which can bias study results (i.e. give us the wrong answer).

My project aims to characterise if and how people at increased genetic risk of dementia differ in terms of their cognitive capability across the whole life course. For example, do people with increased genetic risk of dementia achieve lower grades at school and achieve a lower cognitive peak in early life? Do they start to decline cognitively at an earlier age, or at a faster rate than people who are not at increased genetic risk of dementia? My project also aims to identify causal risk factors for dementia by employing state of the art analytical approaches and by studying many different groups of people (cohorts). Consistent research findings across multiple cohorts of people will not only provide confidence in my findings and yield important insights into true, causal risk factors for dementia, but it will also help to inform dementia prevention strategies.

In summary, the proposed research will help to bring clarity to some of the conflicting literature on dementia risk factors, which in turn will improve translation into public health policies for interventions, with the overriding aim of preventing dementia.

Date proposal received: 
Thursday, 2 November, 2017
Date proposal approved: 
Monday, 13 November, 2017
Keywords: 
Neurology, Addiction - e.g. alcohol, illicit drugs, smoking, gambling, etc., Cognitive impairment, Diabetes, Hypertension, Mental health, Obesity, Respiratory - asthma, Ageing, Biological samples -e.g. blood, cell lines, saliva, etc., Mothers - maternal age, menopause, obstetrics, Metabolic - metabolism, Neurology, Nutrition - breast feeding, diet, Physical - activity, fitness, function, Puberty, Statistical methods, Biomarkers - e.g. cotinine, fatty acids, haemoglobin, etc., Blood pressure, BMI, Cardiovascular, Cohort studies - attrition, bias, participant engagement, ethics, Childhood - childcare, childhood adversity, Cognition - cognitive function, Genetics - e.g. epigenetics, mendelian randomisation, UK10K, sequencing, etc.