ABSTRACT
INTRODUCTION: Stakeholder engagement remains scarce in basic brain research. However, it can greatly improve the relevance of investigations and accelerate the translation of study findings to policy. The Lifebrain consortium investigated risk and protective factors influencing brain health using cognition, lifestyle and imaging data from European cohorts. Stakeholder activities of Lifebrain-organized in a separate work package-included organizing stakeholder events, investigating public perceptions of brain health and dissemination. Here, we describe the experiences of researchers and stakeholders regarding stakeholder engagement in the Lifebrain project. METHODS: Stakeholder engagement in Lifebrain was evaluated through surveys among researchers and stakeholders and stakeholders' feedback at stakeholder events through evaluation forms. Survey data were analysed using a simple content analysis approach, and results from evaluation forms were summarized after reviewing the frequency of responses. RESULTS: Consortium researchers and stakeholders experienced the engagement activities as meaningful and relevant. Researchers highlighted that it made the research and research processes more visible and contributed to new networks, optimized data collection on brain health perceptions and the production of papers and provided insights into stakeholder views. Stakeholders found research activities conducted in the stakeholder engagement work package to be within their field of interest and research results relevant to their work. Researchers identified barriers to stakeholder engagement, including lack of time, difficulties in identifying relevant stakeholders, and challenges in communicating complex scientific issues in lay language and maintaining relationships with stakeholders over time. Stakeholders identified barriers such as lack of budget, limited resources in their organization, time constraints and insufficient communication between researchers and stakeholders. CONCLUSION: Stakeholder engagement in basic brain research can greatly benefit researchers and stakeholders alike. Its success is conditional on dedicated human and financial resources, clear communication, transparent mutual expectations and clear roles and responsibilities. PUBLIC CONTRIBUTION: Patient organizations, research networks, policymakers and members of the general public were involved in engagement and research activities throughout the project duration.
Subject(s)
Health Services Research , Stakeholder Participation , Humans , Health Services Research/methods , Communication , Translational Research, Biomedical , BrainABSTRACT
BackgroundPerinatal exposure to glucocorticoids and elevated endogenous glucocorticoid levels during childhood can have detrimental effects on the developing brain. Here, we examined the impact of glucocorticoid treatment during childhood on brain volumes.MethodsA total of 30 children and adolescents with rheumatic or nephrotic disease previously treated with glucocorticoids and 30 controls matched on age, sex, and parent education underwent magnetic resonance imaging (MRI) of the brain. Total cortical gray and white matter, brain, intracranial volume, and total cortical thickness and surface area were derived from MRI scans.ResultsPatients had significantly smaller gray and white matter and total brain volumes relative to healthy controls. Brain volume differences disappeared when accounting for intracranial volume, as patients had relatively smaller intracranial volumes. Group differences were mainly driven by the children with rheumatic disease. Total cortical thickness and cortical surface area did not significantly differ between groups. We found no significant associations between glucocorticoid-treatment variables and volumetric measures.ConclusionObserved smaller total brain, cortical gray, and white matter volumes in children and adolescents previously treated with glucocorticoids compared with that in healthy controls may reflect both developmental and degenerative processes. Prospective longitudinal studies are warranted to clarify whether findings are related to treatment or disease.
Subject(s)
Brain/drug effects , Glucocorticoids/adverse effects , Glucocorticoids/therapeutic use , Kidney Diseases/drug therapy , Rheumatic Diseases/drug therapy , White Matter/pathology , Adolescent , Brain/diagnostic imaging , Brain/pathology , Case-Control Studies , Child , Female , Humans , Image Processing, Computer-Assisted , Linear Models , Male , Nephrotic Syndrome/drug therapy , Pattern Recognition, AutomatedABSTRACT
Heightened levels of glucocorticoids in children and adolescents have previously been linked to prolonged changes in the diurnal regulation of the stress-hormone cortisol, a glucocorticoid regulated by the hypothalamic-pituitary-adrenal-axis (HPA-axis). To address this question, we examined the salivary cortisol awakening response (CAR) and daily cortisol output in 36 children and adolescents (25 girls/11 boys) aged 7-16 years previously treated with glucocorticoids for nephrotic syndrome or rheumatic disorder and 36 healthy controls. Patients and controls did not significantly differ in the CAR or diurnal cortisol output; however, sex-dependent group differences were observed. Specifically, female patients had a higher CAR relative to female controls, while male patients had higher daily cortisol levels compared to male controls. Notably, CAR in female patients and daily cortisol levels in male patients showed a positive linear relationship with the mean daily glucocorticoid doses administered during treatment. The observed dose-response associations suggest that glucocorticoid therapy during childhood and adolescence might trigger long-term changes in HPA-axis regulation, which may differ for males and females.
Subject(s)
Circadian Rhythm/physiology , Glucocorticoids/pharmacology , Hydrocortisone/metabolism , Adolescent , Child , Circadian Rhythm/drug effects , Dose-Response Relationship, Drug , Female , Humans , Male , Nephrotic Syndrome/drug therapy , Rheumatic Diseases/drug therapy , Sex FactorsABSTRACT
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.
Subject(s)
Aging/physiology , Brain/diagnostic imaging , Brain/physiology , Genotype , Aging/genetics , Birth Weight , Cross-Sectional Studies , Genome-Wide Association Study , Humans , Longitudinal Studies , Magnetic Resonance ImagingABSTRACT
BACKGROUND AND OBJECTIVES: A healthy brain is central to physical and mental well-being. In this multi-site, qualitative study, we investigated views and attitudes of adult participants in brain research studies on the brain and personalized brain health as well as interest in maintaining a healthy brain. DESIGN AND METHODS: We conducted individual interviews with 44 adult participants in brain research cohorts of the Lifebrain consortium in Spain, Norway, Germany, and the United Kingdom. The interviews were audio recorded, transcribed, and coded using a cross-country codebook. The interview data were analyzed using qualitative content analysis. RESULTS: Most participants did not focus on their own brain health and expressed uncertainty regarding how to maintain it. Those actively focusing on brain health often picked one specific strategy like diet or memory training. The participants were interested in taking brain health tests to learn about their individual risk of developing brain diseases, and were willing to take measures to maintain their brain health if personalized follow-up was provided and the measures had proven impact. The participants were interested in more information on brain health. No differences in responses were identified between age groups, sex, or countries. DISCUSSION AND IMPLICATIONS: Concise, practical, personalized, and evidence-based information about the brain may promote brain health. Based on our findings, we have launched an ongoing global brain health survey to acquire more extensive, quantitative, and representative data on public perception of personalized brain health.