The relation among aging, dopamine-regulating genes, and neurocognition

When people are getting old, they often feel increasingly harder to concentrate, and become slower and more inflexible during tasks that involve focused attention, information maintenance in the face of distractions, and when fast switching according to changing goals is required. These cognitive functions are collectively referred to as working memory (WM). Both cross-sectional and longitudinal studies have reported WM impairment in aging. Moreover, aging is accompanied by alterations in brain structure, brain function, and dopaminergic neurotransmission. This thesis sought to link WM to brain structure, brain function, and dopamine (DA)-related genes in large samples of younger and older adults. The chief aims were to provide neural and genetic evidence to increase our understanding of the mechanisms of age-related deficits in WM. The DRD2/ANKK1-Taq1A polymorphism has been associated with DA D2 receptor densities in caudate. In study I, we investigated the effects of this polymorphism on grey-matter (GM) volume in striatum in older adults, and examined whether the genetic effect interacts with age. Results showed that the A allele of the DRD2/ANKK1-Taq1A polymorphism was associated with smaller GM volume in caudate and this effect was only observed in older adults (>72 years). The DRD2-C957T polymorphism has been linked to DA D2 receptor densities in both striatum and extrastriatal areas, such as in prefrontal cortex (PFC). In study II, we investigated the genetic effects of two DRD2 polymorphisms on WM functioning and examined how these effects may interact with adult age. In comparing younger and older adults, we found that the old had lower caudate activity in a highly demanding WM task. In addition, there were single and joint genetic effects of the two DRD2 polymorphisms on WM performance and frontostriatal brain activity. The genetic effects on brain function were observed in older, but not in younger adults, suggesting magnified genetic effects in aging. In study III, we related white-matter integrity with WM performance in a large sample across a wide age range. Results demonstrated that WM was associated with white-matter integrity in multiple tracts, indicating that WM functioning relies on global structural connections among multiple brain regions. Moreover, white-matter integrity could partially account for the age-related difference in WM. The COMT-Val158Met polymorphism has been associated with PFC DA levels. In this study, we found genetic effects of COMT on white-matter microstructure, suggesting a relation between dopaminergic function and white-matter integrity. In study IV, we investigated changes of white-matter integrity and WM performance using longitudinal data. We found that white-matter integrity declined across 10 years in the whole sample (25-80 years) and the decline was greater for older than for younger adults, reflecting a non-linear relation between age and white matter. More importantly, we found change – change associations of white-matter integrity and WM performance in several tracts including genu and body of corpus callosum and superior longitudinal fasciculus, suggesting that impaired WM performance in aging might reflect age-related decrease of white-matter integrity in these tracts. Collectively, these studies demonstrate age-related differences and changes in brain structure and brain function associated with impaired WM performance in aging. The findings support and extend previous work on the roles of DA in WM functioning and brain integrity in aging, and contribute to our understanding of neural and genetic correlates of WM, and how these are affected in aging

Theory-based Explorations of Associations between Human Brain Structure and Intelligence from Childhood to Early Adulthood

Intelligence is often defined as the ability of an agent to learn, adapt to its environment, and solve novel challenges. However, despite over 100 years of theoretical development (e.g., general intelligence), widespread explanatory power (up to 50% of variance in cognitive scores), and the ability of intelligence measures to predict important life outcomes such as educational achievement and mortality, the exact configuration and neural correlates of cognitive ability remain poorly understood. This dissertation aims to make progress in this pursuit by exploring how human brain structure and intelligence correlate and co-develop with each other from childhood to early adulthood (ages 5 – 22 years). This endeavour is undertaken in three large cohorts (N range: 337 – 2072), guided by theory (e.g., crystallised and fluid intelligence), and implemented using rigorous, cutting-edge quantitative methods (i.e., structural equation modelling and network science). The results of this research provide robust evidence that the brain-behaviour relationships in intelligence are complex (i.e., consists of many independent yet interacting parts) and change nonlinearly during development. The first study sought to elucidate the factorial structure and white matter substrates of child and adolescent intelligence using two cross-sectional, developmental samples (CALM: N = 551 (N = 165 neuroimaging), age range: 5 – 18 years; NKI-Rockland: N = 337 (N = 65 neuroimaging), age range: 6 – 18 years). In both samples, it was found (using structural equation modelling (SEM)) that cognitive ability is best modelled as two separable yet related constructs, crystallised and fluid intelligence, which became more distinct (i.e., less correlated) across development, in line with the age differentiation hypothesis. Further analyses revealed that white matter microstructure, most prominently of the superior longitudinal fasciculus, was strongly associated with crystallised (gc) and fluid (gf) abilities. Finally, SEM trees, which combines traditional SEM with decision trees, provided evidence for developmental reorganisation of gc and gf and their white matter substrates such that the relationships among these factors dropped between ages 7 – 8 years before increasing around age 10. Together, these results suggested that shortly before puberty marks a pivotal phase of change in the neurocognitive architecture of intelligence. The second study builds upon the first by again examining the neurocognitive structure of intelligence, this time from a network perspective. The network or mutualism theory of intelligence presupposes direct (statistical) interactions among cognitive abilities (e.g., maths, memory, and vocabulary) throughout development. Therefore, this project used network analytic methods (specifically graphical LASSO) to simultaneously model brain-behaviour relationships essential for general intelligence in a large (behavioural, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165), developmental (ages 5 – 18 years) cohort of struggling learners (CALM). Results indicated that both the single-layer (cognitive or neural nodes) and multilayer (combined cognitive and neural variables) networks consisted of mostly positive, small partial correlations, providing further support for the mutualism/network theory of cognitive ability. Moreover, using community detection (i.e., the Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), convergent evidence suggested that subsets of both cognitive and neural nodes play an intermediary role ‘between’ brain and behaviour. Overall, these findings suggest specific behavioural and neural variables that may have greater influence among (or might be more influenced by) other nodes within general intelligence. The final study investigated the longitudinal relationships between human cortical grey matter structure and measures of decision-making, risk-related behaviours, and spatial working memory from adolescence to early adulthood (ages 14 – 22 years). In the IMAGEN study (maximum N across time points/waves = 2072), latent growth curve models were used to estimate the baseline and longitudinal associations between behavioural measures and cortical surface area, thickness, and volume. Univariate models (only behavioural or neural measures) revealed that performance in decision-making, risk-related behaviours, and spatial working memory, as well as brain structure changed nonlinearly from mid-adolescence (age 14) to early adulthood (age 22). Furthermore, bivariate models (combined behavioural and neural measures) provided evidence for adaptive reorganisation (behaviour intercept predicts changes in brain structure) but not structural scaffolding (brain structure intercept predicts changes in behaviour). Furthermore, findings suggested that there were no correlated changes between behavioural and brain structure slopes (rates of change from mid-adolescence to early adulthood). This dissertation concludes by summarising the core results, addressing key limitations, and discussing avenues for future research. Taken together, this thesis hopes to convince cognitive neuroscientists that to understand cognitive ability and its neural determinants, they (we) must work more diligently toward building coherent, rigorous, and testable neurocognitive theories of intelligence—particularly under the conceptual and analytic paradigm of complex systems.The Cambridge Commonwealth, European & International Trus

Discovering markers of healthy aging:a prospective study in a Danish male birth cohort

There is a pressing need to identify markers of cognitive and neural decline in healthy late-midlife participants. We explored the relationship between cross-sectional structural brain-imaging derived phenotypes (IDPs) and cognitive ability, demographic, health and lifestyle factors (non-IDPs). Participants were recruited from the 1953 Danish Male Birth Cohort (N=193). Applying an extreme group design, members were selected in 2 groups based on cognitive change between IQ at age ~20y (IQ-20) and age ~57y (IQ-57). Subjects showing the highest (n=95) and lowest (n=98) change were selected (at age ~57) for assessments on multiple IDPs and non-IDPs. We investigated the relationship between 453 IDPs and 70 non-IDPs through pairwise correlation and multivariate canonical correlation analysis (CCA) models. Significant pairwise associations included positive associations between IQ-20 and gray-matter volume of the temporal pole. CCA identified a richer pattern - a single "positive-negative" mode of population co-variation coupling individual cross-subject variations in IDPs to an extensive range of non-IDP measures (r = 0.75, Pcorrected < 0.01). Specifically, this mode linked higher cognitive performance, positive early-life social factors, and mental health to a larger brain volume of several brain structures, overall volume, and microstructural properties of some white matter tracts. Interestingly, both statistical models identified IQ-20 and gray-matter volume of the temporal pole as important contributors to the inter-individual variation observed. The converging patterns provide novel insight into the importance of early adulthood intelligence as a significant marker of late-midlife neural decline and motivates additional study

THE DEFAULT MODE NETWORK AND EXECUTIVE FUNCTION: INFLUENCE OF AGE, WHITE MATTER CONNECTIVITY, AND ALZHEIMER’S PATHOLOGY

The default mode network (DMN) consists of a set of interconnected brain regions supporting autobiographical memory, our concept of the self, and the internal monologue. These processes must be maintained at all times and consume the highest amount of the brain’s energy during its baseline state. However, when faced with an active, externally-directed cognitive task, the DMN shows a small, but significant, decrease in activity. The reduction in DMN activity during the performance of an active, externally-directed task compared to a baseline state is termed task-induced deactivation (TID), which is thought to ‘free-up’ resources required to respond to external demands. However, older adults show a reduced level of TID in the DMN. Recently, it has begun to be appreciated that this decrease in TID may be associated with poorer cognitive performance, especially during tasks placing high demands on executive function (EF). Diminished DMN TID has not only been associated with increasing age but also with multiple age-related neurobiological correlates such as accumulating Alzheimer’s disease (AD) pathology and reductions in white matter (WM) connectivity. However, these biological factors—age, WM connectivity reductions and increasing AD pathology—are themselves related. Based on the literature, we hypothesized that declining WM connectivity may represent a common pathway by which both age and AD pathology contribute to diminished DMN TID. Further, we hypothesized that declines in DMN function and WM connectivity would predict poorer in EF. Three experiments were carried out to test these hypotheses. Experiment 1 tested whether WM connectivity predicted the level of DMN TID during a task requiring a high level of EF. Results from 117 adults (ages 25-83) showed that WM connectivity declined with increasing age, and that this decline in WM connectivity was directly associated with reduced DMN TID during the task. Experiment 2 tested whether declines in WM connectivity explained both age-related and AD pathology-related declines in DMN TID. Results from 29 younger adults and 35 older adults showed that declining WM connectivity was associated with increasing age and AD pathology, and that this decline in WM connectivity was a common pathway for diminished DMN TID associated with either aging or AD pathology. Experiment 3 investigated whether measures of WM connectivity and DMN TID at baseline could predict EF measured using clinically-used tests. Results from 29 older adults from Experiment 2 showed that less DMN TID predicted poorer EF at baseline and diminished WM connectivity at baseline predicted a greater decline in EF after 3 years. Further, WM connectivity explained reductions in EF predicted by baseline AD pathology, as well as further reductions in EF not predicted by baseline AD pathology. Together the results of these studies suggest that WM connectivity is a key pathway for age-related and AD pathology-related patterns of diminished DMN TID associated with poorer EF. Further, WM connectivity may represent a potential therapeutic target for interventions attempting to prevent future declines in EF occurring in aging and AD

Distinct aspects of frontal lobe structure mediate age-related differences in fluid intelligence and multitasking.

Ageing is characterized by declines on a variety of cognitive measures. These declines are often attributed to a general, unitary underlying cause, such as a reduction in executive function owing to atrophy of the prefrontal cortex. However, age-related changes are likely multifactorial, and the relationship between neural changes and cognitive measures is not well-understood. Here we address this in a large (N=567), population-based sample drawn from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data. We relate fluid intelligence and multitasking to multiple brain measures, including grey matter in various prefrontal regions and white matter integrity connecting those regions. We show that multitasking and fluid intelligence are separable cognitive abilities, with differential sensitivities to age, which are mediated by distinct neural subsystems that show different prediction in older versus younger individuals. These results suggest that prefrontal ageing is a manifold process demanding multifaceted models of neurocognitive ageing

Neuroplasticity of language networks in aphasia: advances, updates, and future challenges

Researchers have sought to understand how language is processed in the brain, how brain damage affects language abilities, and what can be expected during the recovery period since the early 19th century. In this review, we first discuss mechanisms of damage and plasticity in the post-stroke brain, both in the acute and the chronic phase of recovery. We then review factors that are associated with recovery. First, we review organism intrinsic variables such as age, lesion volume and location and structural integrity that influence language recovery. Next, we review organism extrinsic factors such as treatment that influence language recovery. Here, we discuss recent advances in our understanding of language recovery and highlight recent work that emphasizes a network perspective of language recovery. Finally, we propose our interpretation of the principles of neuroplasticity, originally proposed by Kleim and Jones (1) in the context of extant literature in aphasia recovery and rehabilitation. Ultimately, we encourage researchers to propose sophisticated intervention studies that bring us closer to the goal of providing precision treatment for patients with aphasia and a better understanding of the neural mechanisms that underlie successful neuroplasticity.P50 DC012283 - NIDCD NIH HHSPublished versio

Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines

BACKGROUND: Aging-related cognitive decline is a primary risk factor for Alzheimer’s disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias. METHODS: Using structural and diffusion brain MRI data from the UK Biobank (UKB; N = 8,185, ages 45–78 years), we examined aging of regional grey matter volumes (nodes) and white matter structural connectivity (edges) within nine well-characterized networks-of-interest in the human brain connectome. In the independent Lothian Birth Cohort 1936 (LBC1936; N = 534, all age 73 years), we tested whether aging-sensitive connectome elements are enriched for key domains of cognitive function, before and after controlling for early-life cognitive ability. RESULTS: In UKB, age-differences in individual connectome elements corresponded closely with principal component loadings reflecting connectome-wide integrity (|r(nodes)| = 0.420; |r(edges)| = 0.583), suggesting that connectome aging occurs on broad dimensions of variation in brain architecture. In LBC1936, composite indices of node integrity were predictive of all domains of cognitive function, whereas composite indices of edge integrity were associated specifically with processing speed. Elements within the Central Executive network were disproportionately predictive of late-life cognitive function relative to the network’s small size. Associations with processing speed and visuospatial ability remained after controlling for childhood cognitive ability. CONCLUSIONS: These results implicate global dimensions of variation in the human structural connectome in aging-related cognitive decline. The Central Executive network may demarcate a constellation of elements that are centrally important to age-related cognitive impairments

Neuroprotective Effects of Cardiorespiratory Fitness on White Matter Integrity and Cognition Across the Adult Lifespan

Objective: Cardiorespiratory fitness (CRF) is associated with decreased risk for cognitive decline. Accumulating evidence has linked CRF to more conserved white matter (WM) integrity and better cognitive performance in older adults. Additional research is needed to determine: (1) which WM tracts are most strongly related to CRF, (2) whether CRF-related benefits on WM translate to enhanced executive functioning (EF), and (3) if the neuroprotective effects of CRF are age-dependent. This study aimed to evaluate CRF as an intervention for modulating decreased WM integrity and EF in aging. Method: Participants were community-dwelling adults (N = 499; ages 20-85) from the open-access Nathan Kline Institute – Rockland Sample (NKIRS) with CRF (bike test), self-report of physical activity, diffusion tensor imaging (DTI), and EF data. Mixed-effect modeling tested the interaction between CRF and age on WM integrity (global and local microstructure). Significant WM tracts were retained for structural equation modeling to determine whether enhanced microstructure mediated a positive relationship between CRF and EF. Results: Among older participants (age 60), CRF was significantly related to stronger whole-brain (z-score slope = 0.11) and local WM integrity within five tracts (z-score slope range = 0.14 – 0.20). In support of the age-dependent hypothesis, the CRF–WM relationship was comparably weaker (z-score slopes 0.11) and more limited (one WM tract) in younger adults. CRF was more consistently related to WM than self-report of physical activity. Although CRF was linked to enhanced WM integrity, its potential benefits on EF were not directly observed. Conclusion: The findings highlight the importance of positive lifestyle factors, such as physical activity, in maintaining brain health in senescence. CRF may selectively preserve a collection of anterior and posterior WM connections related to visuomotor function

MRI detection of brain abnormality in sickle cell disease

Introduction: Over the past decades, neuroimaging studies have clarified that a significant proportion of patients with sickle cell disease (SCD) have functionally significant brain abnormalities. Clinically, structural magnetic resonance imaging (MRI) sequences (T2, FLAIR, diffusion-weighted imaging) have been used by radiologists to diagnose chronic and acute cerebral infarction (both overt and clinically silent), while magnetic resonance angiography and venography have been used to diagnose arteriopathy and venous thrombosis. In research settings, imaging scientists are increasingly applying quantitative techniques to shine further light on underlying mechanisms. Areas covered: From a June 2020 PubMed search of ‘magnetic’ or ‘MRI’ and ‘sickle’ over the previous 5 years, we selected manuscripts on T1-based morphometric analysis, diffusion tensor imaging, arterial spin labeling, T2-oximetry, quantitative susceptibility, and connectivity. Expert Opinion: Quantitative MRI techniques are identifying structural and hemodynamic biomarkers associated with risk of neurological and neurocognitive complications. A growing body of evidence suggests that these biomarkers are sensitive to change with treatments, such as blood transfusion and hydroxyurea, indicating that they may hold promise as endpoints in future randomized clinical trials of novel approaches including hemoglobin F upregulation, reduction of polymerization, and gene therapy. With further validation, such techniques may eventually also improve neurological and neurocognitive risk stratification in this vulnerable population

Mapping Genetic Influence on Brain Structure

Neuroimaging is playing an increasingly crucial role in delineating pathological conditions that cannot be typically defined by non-specific clinical symptom. The goal of this thesis was to characterize the genetic influence on grey and white matter indices and evaluate their potential as a reliable “structural MRI signatures”. We first assessed the effects of spatial resolution and smoothing on heritability estimation (Chapter 3). We then investigated heritability patterns of MRI measures of grey and white matter (Chapters 4-5). We then performed a cross-sectional evaluation of how heritability changes over the lifespan for both grey and white matter (Chapter 6). Finally, multivariate structural equation modeling was used to investigate the genetic correlation between grey matter structure and white matter connectivity (Chapter 7), in the default mode network (DMN). Our results show that several key brain structures were moderate to highly heritable and that this heritability was both spatially and temporally heterogeneous. At a network level, the DMN was found to have distinct genetic factors that modulated the grey matter regions and white matter tracts separately. We conclude that the spatial and temporal heterogeneity are likely to reflect gene expression patterns that are related to the developmental of specific brain regions and circuits over time