Trajectories of imaging markers in brain aging: the Rotterdam Study

With aging, the brain undergoes several structural changes. These changes reflect the normal aging process and are therefore not necessarily pathologic. In fact, better understanding of these normal changes is an important cornerstone to also disentangle pathologic changes. Several studies have investigated normal brain aging, both cross-sectional and longitudinal, and focused on a broad range of magnetic resonance imaging (MRI) markers. This study aims to comprise the different aspects in brain aging, by performing

The influence of diet and metabolism on hippocampus and hypothalamus connectivity across the lifespan

The high prevalence of unhealthy dietary patterns, obesity, and related brain disorders such as dementia emphasise the importance of research that examines the effect of dietary and metabolic factors on brain health. Using magnetic resonance imaging (MRI) to assess brain grey matter functional connectivity (FC) and volumes, this thesis aimed to examine the relationship between measures of diet and metabolism and the brain over the adult lifespan. First, a systematic review was conducted, to examine the relationship between dietary and metabolic health in relation to a wide range of brain MRI markers. The reviewed evidence suggested that lower dietary and metabolic health quality was related to reduced brain volume and connectivity, especially in the default mode network and the frontal and temporal lobes, although there were contrasting trends for each of these associations. To address the gaps identified by the review, we examined the association between dietary and metabolic health in relation to the hippocampus and hypothalamus FC and volumes in the cross-sectional Human Connectome Project cohort of 400 younger adults and in the longitudinal Whitehall II cohort of 775 midlife-older aged adults. The Whitehall cohort had longitudinal measures of diet/metabolic markers collected every 5 years throughout their midlife (40-70 years old). First, we note that different dietary and metabolic markers have unique patterns of longitudinal trajectories from mid-to-old-age. Our findings supported the hypothesis that better dietary and metabolic health is associated with volumetric and FC differences of the hippocampus and the hypothalamus both in younger and older cohorts. Specifically, dietary and metabolic health was linked to (1) hippocampal FC with the frontal lobe, precentral gyrus, and occipital lobe and (2) hypothalamic FC with the brainstem and the basal forebrain. These findings contribute to a growing understanding of the brain networks associated with dietary and metabolic health. The thesis provides insights into when in life dietary and metabolic health measures are related to brain health. Our findings indicated that in order to promote brain health in older age, some metabolic factors may be better targeted in midlife (e.g., cholesterol, diet, abdominal fat), while other factors should be targeted as early as possible (blood pressure, body composition/BMI). This may have implications for preventative lifestyle interventions to reduce the risk of developing dementia and to maintain overall brain health

Quantifying structural changes in the ageing brain from magnetic resonance imaging

Understanding the ageing process is of increasing importance to an ageing society and one aspect of this is investigating what role the brain has in this process. Cognitive ability declines as we age and it is one of the most distressing aspects of getting older. Brain tissue deterioration is a significant contributor to lower cognitive ability in late life but the underlying biological mechanisms in the brain are not yet fully understood. One reason for this is the difficulty in obtaining accurate measures of potential ageing-related brain biomarkers. The chapters in this thesis explore the difficulties of quantifying brain changes in the ageing brain from Magnetic Resonance Imaging (MRI), and how the changes identified are related to cognition in later life. The data was acquired as part of the second wave of the longitudinal Lothian Birth Cohort 1936 study in which 866 people aged 73 years, returned for cognitive and medical assessment. At this stage of the study 702 underwent MR imaging resulting in 627 complete datasets across all testing. The entire data, a randomly chosen subset of 150 and 416 freely available data were used to investigate global and regional measurement methods in older brains and how the resultant measurements related to cognitive performance. Furthermore the presence of early life cognitive data in the form of a general intelligence test sat at age 11, served as an indicator of cognitive ability prior to the potential influence of the ageing process. The chapters concerning global measures at first establish, that a measure of intracranial volume (ICV) serves as both a way of correcting for individual differences in brain size between participants and as a proxy premorbid measure of brain size. The analysis, utilising freely available cross-sectional MRI data (http://www.oasis-brains.org) revealed that ICV differed very little between 18-28 year olds and 84-96 year olds where as total brain tissue volume (TBV) differed by 14.1% between the two groups, which was more than twice the standard deviation across the entire age range (18-96 years). Second a validated, reliable method for measuring ICV was investigated using 150 people randomly chosen from the LBC1936 study. Automated and semi-automated methods were validated against reference measurements the results of which showed that common ageing features make automated and semi-automated methods that do not have an additional manual editing step, ineffective at producing accurate ICV measurements. This analysis also highlighted the need to employ additional spatial overlap assessment to volumetric comparison of measurement methods to reduce the effect of false-positives and false-negatives skewing apparent discrepancies between methods. Using the information gained here ICV and TBV from the entire LBC1936 cohort were analysed in a structural equation model, alongside cognitive ability measures at both age 11 and age 73. We found that TBV was a stronger predictor of later life cognitive ability, after accounting for early life ability, but that a modest association remained between ICV and late life cognition. This suggests that early life factors pay a role in how well we age, though the relationship is complex. The regional measures chapters look at two brain regions commonly associated with ageing, the hippocampus and the frontal lobes. Measuring either of these brain regions in large samples of healthy older adults is challenging for many reasons. The hippocampus is small and as with all brain regions shows greater variation in older age, this makes employing automated methods that have the advantage of being fast and reproducible difficult. Following the results of our systematic review of automated methods for measuring the hippocampus, the two most commonly used and available automated methods were validated against reference standard measurements. The results indicated that although automated methods present an attractive alternative to laborious manual measurements they still require manual editing to produce accurate measurements in older adults. The modified strategy employed across the LBC1936 was to use an automated method and then manually edit the output; these segmentations were used to investigate the potential of multimodal image analysis in clarifying associations between the hippocampus and cognitive ability in old age. The analysis focused on associations between longitudinal relaxation time (T1), magnetization transfer ratio (MTR), fractional anisotropy (FA) and mean diffusivity (MD) in the hippocampus and general factors of fluid intelligence, cognitive processing speed and memory. The findings show that multi-modal MRI assessments were more sensitive than volumetric measurements at detecting associations with cognitive measures. The difficulty with producing a relevant frontal lobe measure was made apparent when the result of a large systematic review looking at the manual protocols used revealed 19 methods and 15 different landmarks had been employed. This resulted in an analysis that took the 5 most common boundaries reported and applied them to 10 randomly selected participants from the LBC1936. The results showed significant differences between the resultant volumes, with the smallest measurement when using the genu as the posterior marker representing only 35% of the measurement acquired using the central sulcus. The results from the studies presented in this thesis strongly highlight the need to develop age specific methods when using brain MRI to study ageing. Furthermore the implications of using unstandardised protocols, making assumptions about a methods performance based on validation in younger samples and the need to account for early life factors in this area of research have been made clearer. Studies building on these findings will be beneficial in elucidating the role of the brain in ageing

Decline variability of cortical and subcortical regions in aging: a longitudinal study

Describing the trajectories of age-related change for different brain structures has been of interest in many recent studies. However, our knowledge regarding these trajectories and their associations is still limited due to small sample sizes and low numbers of repeated measures. For the present study, we used a large longitudinal dataset (four measurements over 4 years) comprising anatomical data from a sample of healthy older adults (N = 231 at baseline). This dataset enables us to gain new insights about volumetric cortical and subcortical changes and their associations in the context of healthy aging. Brain structure volumes were derived from T1-weighted MRI scans using FreeSurfer segmentation tools. Brain structure trajectories were fitted using mixed models and latent growth curve models to gain information about the mean extent and variability of decline trajectories for different brain structures as well as the associations between individual trajectories. On the group level, our analyses indicate similar linear changes for frontal and parietal brain regions, while medial temporal regions showed an accelerated decline with advancing age. Regarding subcortical regions, some structures showed strong declines (e.g., hippocampus), others showed little decline (e.g., pallidum). Our data provide little evidence for sex differences regarding the aforementioned trajectories. Between-person variability of the person-specific slopes (random slopes) was largest in subcortical and medial temporal brain structures. When looking at the associations between the random slopes from each brain structure, we found that the decline is largely homogenous across the majority of cortical brain structures. In subcortical and medial temporal brain structures, however, more heterogeneity of the decline was observed, meaning that the extent of the decline in one structure is less predictive of the decline in another structure. Taken together, our study contributes to enhancing our understanding of structural brain aging by demonstrating (1) that average volumetric change differs across the brain and (2) that there are regional differences with respect to between-person variability in the slopes. Moreover, our data suggest (3) that random slopes are highly correlated across large parts of the cerebral cortex but (4) that some brain regions (i.e., medial temporal regions) deviate from this homogeneity

Doctor of Philosophy

dissertationNeurodegenerative diseases are an increasing health care problem in the United States. Quantitative neuroimaging provides a noninvasive method to illuminate individual variations in brain structure to better understand and diagnose these disorders. The overall objective of this research is to develop novel clinical tools that summarize and quantify changes in brain shape to not only help better understand age-appropriate changes but also, in the future, to dissociate structural changes associated with aging from those caused by dementing neurodegenerative disorders. Because the tools we will develop can be applied for individual assessment, achieving our goals could have a significant clinical impact. An accurate, practical objective summary measure of the brain pathology would augment current subjective visual interpretation of structural magnetic resonance images. Fractal dimension is a novel approach to image analysis that provides a quantitative measure of shape complexity describing the multiscale folding of the human cerebral cortex. Cerebral cortical folding reflects the complex underlying architectural features that evolve during brain development and degeneration including neuronal density, synaptic proliferation and loss, and gliosis. Building upon existing technology, we have developed innovative tools to compute global and local (voxel-wise and regional) cerebral cortical fractal dimensions and voxel-wise cortico-fractal surfaces from high-contrast MR images. Our previous research has shown that fractal dimension correlates with cognitive function and changes during the course of normal aging. We will now apply unbiased diffeomorphic atlasing methodology to dramatically improve the alignment of complex cortical surfaces. Our novel methods will create more accurate, detailed geometrically averaged images to take into account the intragroup differences and make statistical inferences about spatiotemporal changes in shape of the cerebral cortex across the adult human lifespan

The Developmental Mismatch in Structural Brain Maturation during Adolescence

Regions of the human brain develop at different rates across the first two decades of life, with some maturing before others. It has been hypothesized that a mismatch in the timing of maturation between subcortical regions (involved in affect and reward processing) and prefrontal regions (involved in cognitive control) underlies the increase in risk-taking and sensation-seeking behaviors observed during adolescence. Most support for this 'dual systems' hypothesis relies on cross-sectional data, and it is not known whether this pattern is present at an individual level. The current study utilizes longitudinal structural magnetic resonance imaging (MRI) data to describe the developmental trajectories of regions associated with risk-taking and sensation-seeking behaviors, namely, the amygdala, nucleus accumbens (NAcc) and prefrontal cortex (PFC). Structural trajectories of gray matter volumes were analyzed using FreeSurfer in 33 participants aged 7-30 years, each of whom had at least three high-quality MRI scans spanning three developmental periods: late childhood, adolescence and early adulthood (total 152 scans). The majority of individuals in our sample showed relatively earlier maturation in the amygdala and/or NAcc compared to the PFC, providing evidence for a mismatch in the timing of structural maturation between these structures. We then related individual developmental trajectories to retrospectively assessed self-reported risk-taking and sensation-seeking behaviors during adolescence in a subsample of 24 participants. Analysis of this smaller sample failed to find a relationship between the presence of a mismatch in brain maturation and risk-taking and sensation-seeking behaviors during adolescence. Taken together, it appears that the developmental mismatch in structural brain maturation is present in neurotypically developing individuals. This pattern of development did not directly relate to self-reported behaviors at an individual level in our sample, highlighting the need for prospective studies combining anatomical and behavioral measures. © 2014 S. Karger AG, Basel

Epigenetic clock as a correlate of anxiety

DNA methylation changes consistently throughout life and age-dependent alterations in DNA methylation can be used to estimate one’s epigenetic age. Post-mortem studies revealed higher epigenetic age in brains of patients with major depressive disorder, as compared with controls. Since MDD is highly correlated with anxiety, we hypothesized that symptoms of anxiety, as well as lower volume of grey matter (GM) in depression-related cortical regions, will be associated with faster epigenetic clock in a community-based sample of young adults. Participants included 88 young adults (53% men; 23–24 years of age) from the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) who participated in its neuroimaging follow-up and provided saliva samples for epigenetic analysis. Epigenetic age was calculated according to Horvath (Horvath, 2013). Women had slower epigenetic clock than men (Cohen’s d = 0.48). In women (but not men), slower epigenetic clock was associated with less symptoms of anxiety. In the brain, women (but not men) with slower epigenetic clock had greater GM volume in the cerebral cortex (brain size-corrected; R2 = 0.07). Lobe-specific analyses showed that in women (but not men), slower epigenetic clock was associated with greater GM volume in frontal lobe (R2 = 0.16), and that GM volume in frontal lobe mediated the relationship between the speed of epigenetic clock and anxiety trait (ab = 0.15, SE = 0.15, 95% CI [0.007; 0.369]). These findings were not replicated, however, in a community-based sample of adolescents (n = 129; 49% men; 12–19 years of age), possibly due to the different method of tissue collection (blood vs. saliva) or additional sources of variability in the cohort of adolescents (puberty stages, socioeconomic status, prenatal exposure to maternal smoking during pregnancy)

Normative data for subcortical regional volumes over the lifetime of the adult human brain

Normative data for volumetric estimates of brain structures are necessary to adequately assess brain volume alterations in individuals with suspected neurological or psychiatric conditions. Although many studies have described age and sex effects in healthy individuals for brain morphometry assessed via magnetic resonance imaging, proper normative values allowing to quantify potential brain abnormalities are needed. We developed norms for volumetric estimates of subcortical brain regions based on cross-sectional magnetic resonance scans from 2790 healthy individuals aged 18 to 94 years using 23 samples provided by 21 independent research groups. The segmentation was conducted using FreeSurfer, a widely used and freely available automated segmentation software. Models predicting subcortical regional volumes of each hemisphere were produced including age, sex, estimated total intracranial volume (eTIV), scanner manufacturer, magnetic field strength, and interactions as predictors. The mean explained variance by the models was 48%. For most regions, age, sex and eTIV predicted most of the explained variance while manufacturer, magnetic field strength and interactions predicted a limited amount. Estimates of the expected volumes of an individual based on its characteristics and the scanner characteristics can be obtained using derived formulas. For a new individual, significance test for volume abnormality, effect size and estimated percentage of the normative population with a smaller volume can be obtained. Normative values were validated in independent samples of healthy adults and in adults with Alzheimer's disease and schizophrenia

Cerebral blood flow measurements with arterial spin labelling in a tri-ethnic population cohort: associations of cardiovascular risk factors and MR imaging markers of brain ageing

Differences in cerebral blood flow (CBF) have been identified between older individuals in good cognitive health and those experiencing cognitive decline and dementia. Previous studies have shown that the aetiology of dementia includes a substantial vascular component and there is evidence that CBF decline in old age may be linked to cardiovascular disease. Although the incidence, prevalence and impact of vascular risk varies by ethnicity and gender, many previous studies have focused on participants of white European origin or have pooled ethnically diverse samples, while differences between sexes have been under-investigated. This thesis used arterial spin labelling (ASL) to measure cortical CBF in an elderly tri-ethnic population cohort and examined its relationship with vascular risk and the brain ageing markers of cortical volume and white matter hyperintensity (WMH) volume from magnetic resonance imaging (MRI). Chapter 4 showed that use of the currently recommended mean haematocrit (Hct) value in equations that calculate CBF from ASL underestimated CBF in women and non-European ethnicities. The alternative method of substituting individually measured Hct into the equation was implemented in the following chapters. Results from Chapter 5 indicated that increased vascular risk factors were associated with lower CBF, but these relationships varied by ethnicity and sex. Ethnicity and sex also modified the strength of associations of increased vascular risk with decreased cortical tissue volume and increased volume of WMHs examined in Chapter 6. However, there was no evidence of any association of CBF with the MRI markers of brain ageing