People's interest in brain health testing: Findings from an international, online cross-sectional survey.

Brain health entails mental wellbeing and cognitive health in the absence of brain disorders. The past decade has seen an explosion of tests, cognitive and biological, to predict various brain conditions, such as Alzheimer's Disease. In line with these current developments, we investigated people's willingness and reasons to-or not to-take a hypothetical brain health test to learn about risk of developing a brain disease, in a cross-sectional multilanguage online survey. The survey was part of the Global Brain Health Survey, open to the public from 4th June 2019 to 31st August 2020. Respondents were largely recruited via European brain councils and research organizations. 27,590 people responded aged 18 years or older and were predominantly women (71%), middle-aged or older (>40 years; 83%), and highly educated (69%). Responses were analyzed to explore the relationship between demographic variables and responses. Results: We found high public interest in brain health testing: over 91% would definitely or probably take a brain health test and 86% would do so even if it gave information about a disease that cannot be treated or prevented. The main reason for taking a test was the ability to respond if one was found to be at risk of brain disease, such as changing lifestyle, seeking counseling or starting treatment. Higher interest in brain health testing was found in men, respondents with lower education levels and those with poor self-reported cognitive health. Conclusion: High public interest in brain health and brain health testing in certain segments of society, coupled with an increase of commercial tests entering the market, is likely to put pressure on public health systems to inform the public about brain health testing in years to come.

Public perceptions of brain health: an international, online cross-sectional survey.

OBJECTIVES: To investigate public perspectives on brain health. DESIGN: Cross-sectional multilanguage online survey. SETTING: Lifebrain posted the survey on its website and social media and shared it with stakeholders. The survey was open from 4 June 2019 to 31 August 2020. PARTICIPANTS: n=27 590 aged ≥18 years from 81 countries in five continents completed the survey. The respondents were predominantly women (71%), middle aged (41-60 years; 37%) or above (>60 years; 46%), highly educated (69%) and resided in Europe (98%). MAIN OUTCOME MEASURES: Respondents' views were assessed regarding factors that may influence brain health, life periods considered important to look after the brain and diseases and disorders associated with the brain. We run exploratory linear models at a 99% level of significance to assess correlates of the outcome variables, adjusting for likely confounders in a targeted fashion. RESULTS: Of all significant effects, the respondents recognised the impact of lifestyle factors on brain health but had relatively less awareness of the role socioeconomic factors might play. Most respondents rated all life periods as important for the brain (95%-96%), although the prenatal period was ranked significantly lower (84%). Equally, women and highly educated respondents more often rated factors and life periods to be important for brain health. Ninety-nine per cent of respondents associated Alzheimer's disease and dementia with the brain. The respondents made a connection between mental health and the brain, and mental disorders such as schizophrenia and depression were significantly more often considered to be associated with the brain than neurological disorders such as stroke and Parkinson's disease. Few respondents (<32%) associated cancer, hypertension, diabetes and arthritis with the brain. CONCLUSIONS: Differences in perceptions of brain health were noted among specific segments of the population. Policies providing information about brain-friendly health behaviours and targeting people less likely to have relevant experience may be needed.

Individual variations in 'brain age' relate to early-life factors more than to longitudinal brain change.

Brain age is a widely used index for quantifying individuals' brain health as deviation from a normative brain aging trajectory. Higher-than-expected brain age is thought partially to reflect above-average rate of brain aging. Here, we explicitly tested this assumption in two independent large test datasets (UK Biobank [main] and Lifebrain [replication]; longitudinal observations ≈ 2750 and 4200) by assessing the relationship between cross-sectional and longitudinal estimates of brain age. Brain age models were estimated in two different training datasets (n ≈ 38,000 [main] and 1800 individuals [replication]) based on brain structural features. The results showed no association between cross-sectional brain age and the rate of brain change measured longitudinally. Rather, brain age in adulthood was associated with the congenital factors of birth weight and polygenic scores of brain age, assumed to reflect a constant, lifelong influence on brain structure from early life. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging.

Scientists who study the brain and aging are keen to find an effective way to measure brain health, which could help identify people at risk for dementia or memory problems. One popular marker is 'brain age'. This measurement uses a brain scan to estimate a person's chronological age, then compares the estimated brain age to the person's actual age to determine whether their brain is aging faster or slower than expected for their age. However, since brain age relies on one brain scan taken at one point in time, it is not clear whether it really measures brain aging or if it might capture brain differences that have been present throughout the individual's life. Studies comparing individual brain scans over several years would be necessary to know for sure. Now, Vidal-Piñeiro et al. show that the brain-age measurement does not reflect faster brain aging. In the experiments, the researchers compared repeated brain scans of thousands of individuals over 40 years of age. The experiments showed that deviations from normative brain age detected in a single scan reflected early life differences more than changes in the brain over time. For example, people with older-looking brains were more likely to have had a low birth weight or to have a combination of genes associated with having an older looking brain. Vidal-Piñeiro et al. show that brain age mostly reflects a pre-existing brain condition rather than brain aging. The experiments also suggest that genetics and early brain development likely have a strong impact on brain health throughout life. Future studies trying to test or develop brain-aging measurements should use serial measurements to track brain changes over time.

The genetic organization of longitudinal subcortical volumetric change is stable throughout the lifespan.

Development and aging of the cerebral cortex show similar topographic organization and are governed by the same genes. It is unclear whether the same is true for subcortical regions, which follow fundamentally different ontogenetic and phylogenetic principles. We tested the hypothesis that genetically governed neurodevelopmental processes can be traced throughout life by assessing to which degree brain regions that develop together continue to change together through life. Analyzing over 6000 longitudinal MRIs of the brain, we used graph theory to identify five clusters of coordinated development, indexed as patterns of correlated volumetric change in brain structures. The clusters tended to follow placement along the cranial axis in embryonic brain development, suggesting continuity from prenatal stages, and correlated with cognition. Across independent longitudinal datasets, we demonstrated that developmental clusters were conserved through life. Twin-based genetic correlations revealed distinct sets of genes governing change in each cluster. Single-nucleotide polymorphisms-based analyses of 38,127 cross-sectional MRIs showed a similar pattern of genetic volume-volume correlations. In conclusion, coordination of subcortical change adheres to fundamental principles of lifespan continuity and genetic organization.

Genetic risk for Alzheimer disease predicts hippocampal volume through the human lifespan.

OBJECTIVE: To test the hypothesis that genetic risk for Alzheimer disease (AD) may represent a stable influence on the brain from early in life, rather than being primarily age dependent, we investigated in a lifespan sample of 1,181 persons with a total of 2,690 brain scans, whether higher polygenic risk score (PGS) for AD and presence of APOE ε4 was associated with lower hippocampal volumes to begin with, as an offset effect, or possibly faster decline in older age. METHODS: Using general additive mixed models, we assessed the relations of PGS for AD, including variants in APOE with hippocampal volume and its change in a cognitively healthy longitudinal lifespan sample (age range: 4-95 years, mean visit age 39.7 years, SD 26.9 years), followed for up to 11 years. RESULTS: AD-PGS and APOE ε4 in isolation showed a significant negative effect on hippocampal volume. The effect of a 1 sample SD increase in AD-PGS on hippocampal volume was estimated to -36.4 mm3 (confidence interval [CI]: -71.8, -1.04) and the effect of carrying ε4 allele(s) -107.0 mm3 (CI: -182.0, -31.5). Offset effects of AD-PGS and APOE ε4 were present in hippocampal development, and interactions between age and genetic risk on volume change were not consistently observed. CONCLUSIONS: Endophenotypic manifestation of polygenic risk for AD may be seen across the lifespan in cognitively healthy persons, not being confined to clinical populations or older age. This emphasizes that a broader population and age range may be relevant targets for attempts to prevent AD.

The Global Brain Health Survey: Development of a Multi-Language Survey of Public Views on Brain Health.

Background: Brain health is a multi-faceted concept used to describe brain physiology, cognitive function, mental health and well-being. Diseases of the brain account for one third of the global burden of disease and are becoming more prevalent as populations age. Diet, social interaction as well as physical and cognitive activity are lifestyle factors that can potentially influence facets of brain health. Yet, there is limited knowledge about the population's awareness of brain health and willingness to change lifestyle to maintain a healthy brain. This paper introduces the Global Brain Health Survey protocol, designed to assess people's perceptions of brain health and factors influencing brain health. Methods: The Global Brain Health Survey is an anonymous online questionnaire available in 14 languages to anyone above the age of 18 years. Questions focus on (1) willingness and motivation to maintain or improve brain health, (2) interest in learning more about individual brain health using standardized tests, and (3) interest in receiving individualized support to take care of own brain health. The survey questions were developed based on results from a qualitative interview study investigating brain health perceptions among participants in brain research studies. The survey includes 28 questions and takes 15-20 min to complete. Participants provide electronically informed consent prior to participation. The current survey wave was launched on June 4, 2019 and will close on August 31, 2020. We will provide descriptive statistics of samples distributions including analyses of differences as a function of age, gender, education, country of residence, and we will examine associations between items. The European Union funded Lifebrain project leads the survey in collaboration with national brain councils in Norway, Germany, and Belgium, Brain Foundations in the Netherlands and Sweden, the National University of Ostroh Academy and the Women's Brain Project. Discussion: Results from this survey will provide new insights in peoples' views on brain health, in particular, the extent to which the adoption of positive behaviors can be encouraged. The results will contribute to the development of policy recommendations for supporting population brain health, including measures tailored to individual needs, knowledge, motivations and life situations.