Evaluating risk of dementia in older people: a pathway to personalized prevention?

Over 40 million people worldwide have dementia, with an estimated global cost of US$1 trillion annually. The number of people with dementia is expected to double every 20 years due to rapid global demographic changes, making dementia one of the largest socioeconomic and health challenges worldwide. Age-standardized rates of dementia are reported to have decreased in several high-income countries over the past 20 years, probably related to successive generations’ higher levels of education, and earlier detection and treatment of illness risk factors. This suggests that dementia can be prevented by modifications to dementia risk factors, with recent evidence showing that feasible interventions targeting some of these risk factors could result in savings of £1.9 billion per year in England. That ‘prevention is better than care’ is even clearer in the light of repeated failures of novel drug approaches to treating established dementia. However, while we have strong evidence for a causal relationship for many risk factors for dementia, there is still very limited evidence that we can actually prevent it, so future approaches are likely to require personalized prevention, meaning that it will need to be targeted towards the right risk factors in the right people. In this issue of the European Heart Journal, Rasmussen and colleagues aim to develop risk score tools to identify people at high risk of developing dementia according to established genetic and lifestyle factors. Two large Danish cohorts were combined to generate a sample of >60 000 people who were followed for up to 25 years, and a combination of traditional statistical approaches and machine learning was used to identify the strongest predictors of dementia risk from a shortlist of candidates: age, sex, education, diabetes, hypertension, smoking status, and genetic risk according to both apolipoprotein E (APOE) genotype and a polygenic score (Figure 1). These were then incorporated in predictive statistical models which accounted for the competing possibility of dying before dementia development to give the probability of developing dementia during 10 years according to risk factor status. The authors then created a series of colour-coded charts indicating that, for example, a nonsmoking man aged 50–59 years with high educational attainment, no diabetes, and favourable genetic profile has a <1% chance of developing dementia during the subsequent 10 years, whereas a female smoker aged over 80, with limited education, diabetes, two APOE e4 alleles, and a high number of risk genes has a 66% chance of developing dementia over the next decade. Several previous risk scores have been developed for dementia either to guide prevention or to support identification of people for more detailed assessment, but this study’s approach has methodological strengths and includes a more comprehensive range of risk factors. The generation for the first time of dementia risk charts, akin to those used for cardiovascular risk from the Framingham study, is a potentially important step forward as it facilitates the identification of high-risk individuals based on a range of risk factors, which could help to target prevention towards those who need it most. This is particularly important as some recent multicomponent trials aimed at preventing dementia found that the most benefit was in those who had the highest baseline risk, so more targeted prevention could yield greater impact. Focusing on potentially modifiable risk factors for dementia could also promote a positive public health message related to the potential modification of dementia risk by changing risk factors. The pessimism felt by those who assume that dementia is an inevitable consequence of ageing, or that a positive family history of dementia indicates that they will follow the same disease course, is misplaced according to this study and previous research which have shown the likely modifiability of dementia risk with positive lifestyle approaches, even in the face of unmodifiable age, genotype, and sex. Perhaps stopping smoking and effective diabetes management in the woman described above may reduce her risk from 66% to 55%?