44 research outputs found

    Cortical gyrification in relation to age and cognition in older adults

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    Gyrification of the cerebral cortex changes with aging and relates to development of cognitive function during early life and midlife. Little is known about how gyrification relates to age and cognitive function later in life. We investigated this in 4397 individuals (mean age: 63.5 years, range: 45.7 to 97.9) from the Rotterdam Study, a population-based cohort. Global and local gyrification were assessed from T1-weighted images. A measure for global cognition, the g-factor, was calculated from five cognitive tests. Older age was associated with lower gyrification (mean difference per year ​= ​−0.0021; 95% confidence interval ​= ​−0.0025; −0.0017). Non-linear terms did not improve the models. Age related to lower gyrification in the parietal, frontal, temporal and occipital regions, and higher gyrification in the medial prefrontal cortex. Higher levels of the g-factor were associated with higher global gyrification (mean difference per g-factor unit ​= ​0.0044; 95% confidence interval ​= ​0.0015; 0.0073). Age and the g-factor did not interact in relation to gyrification (p ​> ​0.05). The g-factor bilaterally associated with gyrification in three distinct clusters. The first cluster encompassed the superior temporal gyrus, the insular cortex and the postcentral gyrus, the second cluster the lingual gyrus and the precuneus, and the third cluster the orbitofrontal cortex. These clusters largely remained statistically significant after correction for cortical surface area. Overall, the results support the notion that gyrification varies with aging and cognition during and after midlife, and suggest that gyrification is a potential marker for age-related brain and co

    Multivariate Analysis and Modelling of multiple Brain endOphenotypes: Let's MAMBO!

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    Imaging genetic studies aim to test how genetic information influences brain structure and function by combining neuroimaging-based brain features and genetic data from the same individual. Most studies focus on individual correlation and association tests between genetic variants and a single measurement of the brain. Despite the great success of univariate approaches, given the capacity of neu- roimaging methods to provide a multiplicity of cerebral phenotypes, the development and application of multivariate methods become crucial. In this article, we review novel methods and strategies focused on the analysis of multiple phenotypes and genetic data. We also discuss relevant aspects of multi-trait modelling in the context of neuroimag- ing data

    The interaction of cognitive and brain reserve with frailty in the association with mortality : an observational cohort study

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    Background A higher cognitive reserve and brain reserve could decrease mortality risk, but the interaction of these factors with general age-related loss of physical fitness (eg, frailty) remains unclear with regards to mortality. We investigated the associations of cognitive and brain reserve with mortality and the interaction of cognitive and brain reserve with frailty within these associations. Methods Within the observational population-based cohort of the Rotterdam Study, we included participants who visited the research centre for a cognitive assessment between March 2, 2009, and March 1, 2012. Participants with an incomplete assessment of cognition, no data on education attainment, no MRI or an MRI of insufficient quality, three or more missing frailty criteria, or a dementia diagnosis were excluded. Participants were followed up until their death or May 1, 2019. Cognitive reserve was defined as a latent variable that captures variance across five cognitive tests. Brain reserve was defined as the proportion of healthy-appearing brain volume relative to total intracranial volume measured with 1.5 Tesla MRI. Frailty was defined according to Fried's frailty phenotype; participants meeting at least one of the five criteria were considered frail. Hazard ratios (HRs) for associations of cognitive reserve, brain reserve, frailty, and reserve-frailty interactions with the risk of mortality were estimated using Cox regression models. Findings 2878 individuals in the Rotterdam Study who visited the research centre for a cognitive assessment were considered eligible. 1388 individuals were excluded due to incomplete or missing data or a dementia diagnosis. 1490 participants with valid information on cognitive reserve, brain reserve, and frailty were included (mean age 74.3 years [SD 5.5]; 815 [55%] female participants). 810 (54%) participants were classified as frail. A higher cognitive reserve (HR 0.87 per SD, 95% CI 0.76-0.99, p=0.036) and a higher brain reserve (0.85 per SD, 0.72-1.00, p=0.048) were associated with a lower risk of mortality, after adjusting for sex, age, educational level, body-mass index, smoking status, and number of comorbidities. The association between cognitive reserve and mortality was more pronounced (0.77 per SD, 0.66-0.90, p=0.0012) when the cognitive reserve-frailty interaction (p=0.0078) was included, indicating that higher cognitive reserve is related to lower mortality in individuals with frailty. The brain reserve frailty interaction was non-significant. Interpretation Higher cognitive reserve and higher brain reserve were associated with a lower mortality risk. Additionally, cognitive reserve and frailty interact in the association with mortality, such that higher cognitive reserve is particularly associated with lower mortality in frail participants. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

    Genetic Burden for Late-Life Neurodegenerative Disease and Its Association With Early-Life Lipids, Brain, Behavior, and Cognition

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    Background: Genetics play a significant role in the etiology of late-life neurodegenerative diseases like Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia. Part of the individual differences in risk for these diseases can be traced back decades before the onset of disease symptoms. Previous studies have shown evidence for plausible links of apolipoprotein E (APOE), the most important genetic marker for Alzheimer’s disease, with early-life cognition and neuroimaging markers. We aimed to assess whether genome-wide genetic burden for the aforementioned neurodegenerative diseases plays a role in early-life processes. Methods: We studied children from the Generation R Study, a prospective birth cohort. APOE genotypes and polygenic genetic burdens for Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia were obtained through genome-wide genotyping. Non-verbal intelligence was assessed through cognitive tests at the research center around the age of 6 years, and educational attainment through a national school performance test around the age of 11 years. The Child Behavior Checklist was administered around the age of 10 years, and data from the anxious/depressed, withdrawn/depressed, and the internalizing behavior problems scales were used. Children participated in a neuroimaging study when they were 10 years old, in which structural brain metrics were obtained. Lipid serum profiles, which may be influenced by APOE genotype, were assessed from venal blood obtained around the age of 6 years. The sample size per analysis varied between 1,641 and 3,650 children due to completeness of data. Results: We did not find evidence that APOE genotype or the polygenic scores impact on childhood nonverbal intelligence, educational attainment, internalizing behavior, and global brain structural measures including total brain volume and whole brain fractional anisotropy (all p > 0.05). Carriership of the APOE ε2 allele was associated with lower and APOE ε4 with higher low-density lipoprotein cholesterol concentrations when compared to APOE ε3/ε3 carriers. Conclusion: We found no evidence that genetic burden for late-life neurodegenerative diseases associates with early-life cognition, internalizing behavior, or global brain structure

    Genetic scores for adult subcortical volumes associate with subcortical volumes during infancy and childhood

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    Individual differences in subcortical brain volumes are highly heritable. Previous studies have identified genetic variants that underlie variation in subcortical volumes in adults. We tested whether those previously identified variants also affect subcortical regions during infancy and early childhood. The study was performed within the Generation R study, a prospective birth cohort. We calculated polygenic scores based on reported GWAS for volumes of the accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus. Participants underwent cranial ultrasound around 7 weeks of age (range: 3–20), and we obtained metrics for the gangliothalamic ovoid, a predecessor of the basal ganglia. Furthermore, the children participated in a magnetic resonance imaging (MRI) study around the age of 10 years (range: 9–12). A total of 340 children had complete data at both examinations. Polygenic scores primarily associated with their corresponding volumes at 10 years of age. The scores also moderately related to the diameter of the gangliothalamic ovoid on cranial ultrasound. Mediation analysis showed that the genetic influence on subcortical volumes at 10 years was only mediated for 16.5–17.6% of the total effect through the gangliothalamic ovoid diameter at 7 weeks of age. Combined, these findings suggest that previously identified genetic variants in adults are relevant for subcortical volumes during early life, and that they affect both prenatal and postnatal development of the subcortical regions

    White matter microstructure correlates of age, sex, handedness and motor ability in a population-based sample of 3031 school-age children

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    Understanding the development of white matter microstructure in the general population is an imperative precursor to identifying its involvement in psychopathology. Previous studies have reported changes in white matter microstructure associated with age and different developmental patterns between boys and girls. Handedness has also been related to white matter in adults. Motor performance, tightly dependent on overall neuronal myelination, has been related to the corpus callosum. However, the association between motor performance and global white matter microstructure has not been reported in the literature. In general, these age, sex, handedness, and motor performance associations have been observed using small and poorly representative samples. We examined the rela

    Design and overview of the Origins of Alzheimer’s Disease Across the Life course (ORACLE) study

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    Brain development and deterioration across the lifespan are integral to the etiology of late-life neurodegenerative disease. Factors that influence the health of the adult brain remain to be elucidated and include risk factors, protective factors, and factors related to cognitive and brain reserve. To address this knowledge gap we designed a life-course study on brain health, which received funding through the EU ERC Programme under the name Origins of Alzheimer’s Disease Across the Life course (ORACLE) Study. The ORACLE Study is embedded within Generation R, a prospective population-based cohort study of children and their parents, and links this with the Rotterdam Study, a population-based study in middle-aged and elderly persons. The studies are based in Rotterdam, the Netherlands. Generation R focuses on child health from fetal life until adolescence with repeated in-person examinations, but has also included data collection on the children’s parents. The ORACLE Study aims to extend the parental data collection in nearly 2000 parents with extensive measures on brain health, including neuroimaging, cognitive testing and motor testing. Additionally, questionnaires on migraine, depressive symptoms, sleep, and neurological family history were completed. These data allow for the investigation of longitudinal influences on adult brain health as well as intergenerational designs involving children and parents. As a secondary focus, the sampling is enriched by mothers (n = 356) that suffered from hypertensive disorders during pregnancy in order to study brain health in this high-risk population. This article provides an overview of the rationale and the design of the ORACLE Study
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