Cortical covariance networks in ageing: Cross-sectional data from the Irish Longitudinal Study on Ageing (TILDA)

The association between kidney function, cognitive function, and structural brain abnormalities in community-dwelling individuals aged 50+ is mediated by age and biomarkers of cardiovascular disease

AIMS

Cognitive impairment has been associated with kidney function and chronic kidney disease. Whether this association is due to accelerated cardiovascular disease (CVD) or an independent specific kidney function effect related to toxins is unclear. We investigated the impact of an array of clinical factors, inflammatory biomarkers, and cardiovascular biomarkers on the association between kidney function, cognitive function, and structural brain abnormalities.

METHODS AND RESULTS

We used data from the first and third waves of the TILDA Study, a population-representative prospective cohort of Irish adults aged 50 years and over, based on stratified random sampling (n = 3774). The MRI sub-study included participants who consented to MRI brain imaging in addition to the health assessment. Multivariable linear and mixed-effect longitudinal regression models were fitted separately for each kidney marker/estimated glomerular filtration rate (eGFR) equation after adjusting for baseline age and demographics, clinical vascular risk factors, and biomarkers. Unadjusted analyses showed an association between low eGFR, cognitive dysfunction, and cognitive decline (P < 0.001 for all kidney markers). Kidney function markers were also associated with white matter disease [OR = 3.32 (95% CI: 1.11, 9.98)], total grey matter volume (β = -0.17, 95% CI -0.27 to -0.07), and regional grey matter volumes within areas particularly susceptible to hypoxia (P < 0.001 for all). All the associations decreased after adjusting for age and were also diminished after adjusting for CVD biomarkers. Age and CVD-biomarker score were significant mediators of the adjusted associations between eGFR and cognitive status. These results remained consistent for cross-sectional and longitudinal outcomes and specific cognitive domains.

CONCLUSION

Decreased kidney function was associated with cerebrovascular disease. The association appeared to be mediated predominantly by age and the combination of CVD markers [namely N-terminal pro-B-type natriuretic peptide (NT-proBNP) and Growth Differentiation Factor 15 (GDF15)], supporting the idea that shared biological pathways underline both diseases. Further mechanistic studies of the specific molecular mechanisms that lead to both kidney and cognitive decline are warranted.

Tooth loss and regional grey matter volume

OBJECTIVES

To investigate whether tooth loss was associated with regional grey matter volume (GMV) in a group of community dwelling older men and women from Ireland.

METHODS

A group of 380 dementia-free men and women underwent a dental examination and had a Magnetic Resonance Imaging (MRI) scan as part of The Irish Longitudinal Study of Aging (TILDA). Cortical parcellation was conducted using Freesurfer utilities to produce volumetric measures of gyral based regions of interest. Analysis included multiple linear regression to investigate the association between tooth loss and regional GMVs with adjustment for various confounders.

RESULTS

The mean age of participants was 68.1 years (SD 7.3) and 51.6% of the group were female. 50 (13.2%) of the participants were edentulous, 148 (38.9%) had 1-19 teeth, and 182 (47.9%) had ≥20 teeth. Multiple liner regression analysis with adjustment for a range of potential confounders showed associations between the number of teeth and GMVs in the paracentral lobule and the cuneus cortex. In the paracentral lobule, comparing participants with 1-19 teeth versus edentates there was an increase in GMV of β=323.0mm³ (95% Confidence Interval [CI] 84.5, 561.6) and when comparing participants with ≥20 teeth to edentates there was an increase of β=382.3mm³ (95% CI 126.9, 637.7). In the cuneus cortex, comparing participants with ≥20 teeth to edentates there was an increase in GMV of β=380.5mm³ (95% CI 69.4, 691.5).

CONCLUSIONS

In this group of older men and women from Ireland, the number of teeth was associated with GMVs in the paracentral lobule and the cuneus cortex independent of various known confounders.

CLINICAL SIGNIFICANCE

Although not proof of causation, the finding that tooth loss was associated with regional reduced GMV in the brain may represent a potential explanatory link to the observed association between tooth loss and cognitive decline.

Connectome-based predictive modelling of cognitive reserve using task-based functional connectivity

Cognitive reserve supports cognitive function in the presence of pathology or atrophy. Functional neuroimaging may enable direct and accurate measurement of cognitive reserve which could have considerable clinical potential. The present study aimed to develop and validate a measure of cognitive reserve using task-based fMRI data that could then be applied to independent resting-state data. Connectome-based predictive modelling with leave-one-out cross-validation was applied to predict a residual measure of cognitive reserve using task-based functional connectivity from the Cognitive Reserve/Reference Ability Neural Network studies (n = 220, mean age = 51.91 years, SD = 17.04 years). This model generated summary measures of connectivity strength that accurately predicted a residual measure of cognitive reserve in unseen participants. The theoretical validity of these measures was established via a positive correlation with a socio-behavioural proxy of cognitive reserve (verbal intelligence) and a positive correlation with global cognition, independent of brain structure. This fitted model was then applied to external test data: resting-state functional connectivity data from The Irish Longitudinal Study on Ageing (TILDA, n = 294, mean age = 68.3 years, SD = 7.18 years). The network-strength predicted measures were not positively associated with a residual measure of cognitive reserve nor with measures of verbal intelligence and global cognition. The present study demonstrated that task-based functional connectivity data can be used to generate theoretically valid measures of cognitive reserve. Further work is needed to establish if, and how, measures of cognitive reserve derived from task-based functional connectivity can be applied to independent resting-state data.

Evaluation of functional MRI-based human brain parcellation: a review

Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.

Hemodynamic and structural brain measures in high and low sedentary older adults

Due to its cardiovascular effects sedentary behaviour might impact cerebrovascular function in the long term, affecting cerebrovascular regulatory mechanisms and perfusion levels. Consequently this could underly potential structural brain abnormalities associated with cognitive decline. We therefore assessed the association between sedentary behaviour and brain measures of cerebrovascular perfusion and structural abnormalities in community-dwelling older adults. Using accelerometery (GENEActiv) data from The Irish Longitudinal Study on Ageing (TILDA) we categorised individuals by low- and high-sedentary behaviour (≤8 vs >8 hours/day). We examined prefrontal haemoglobin oxygenation levels using Near-Infrared Spectroscopy during rest and after an orthostatic challenge in 718 individuals (66 ± 8 years, 52% female). Global grey matter cerebral blood flow, total grey and white matter volume, total and subfield hippocampal volumes, cortical thickness, and white matter hyperintensities were measured using arterial spin labelling, T1, and FLAIR MRI in 86 individuals (72 ± 6 years, 55% female). While no differences in prefrontal or global cerebral hemodynamics were found between groups, high-sedentary individuals showed lower hippocampal volumes and increased white matter hyperintensities compared to their low-sedentary counterparts. Since these structural cerebral abnormalities are associated with cognitive decline and Alzheimer's disease, future work exploring the causal pathways underlying these differences is needed.

Verbal intelligence is a more robust cross-sectional measure of cognitive reserve than level of education in healthy older adults

BACKGROUND

Cognitive reserve is most commonly measured using socio-behavioural proxy variables. These variables are easy to collect, have a straightforward interpretation, and are widely associated with reduced risk of dementia and cognitive decline in epidemiological studies. However, the specific proxies vary across studies and have rarely been assessed in complete models of cognitive reserve (i.e. alongside both a measure of cognitive outcome and a measure of brain structure). Complete models can test independent associations between proxies and cognitive function in addition to the moderation effect of proxies on the brain-cognition relationship. Consequently, there is insufficient empirical evidence guiding the choice of proxy measures of cognitive reserve and poor comparability across studies.

METHOD

In a cross-sectional study, we assessed the validity of 5 common proxies (education, occupational complexity, verbal intelligence, leisure activities, and exercise) and all possible combinations of these proxies in 2 separate community-dwelling older adult cohorts: The Irish Longitudinal Study on Ageing (TILDA; N = 313, mean age = 68.9 years, range = 54-88) and the Cognitive Reserve/Reference Ability Neural Network Study (CR/RANN; N = 234, mean age = 64.49 years, range = 50-80). Fifteen models were created with 3 brain structure variables (grey matter volume, hippocampal volume, and mean cortical thickness) and 5 cognitive variables (verbal fluency, processing speed, executive function, episodic memory, and global cognition).

RESULTS

No moderation effects were observed. There were robust positive associations with cognitive function, independent of brain structure, for 2 individual proxies (verbal intelligence and education) and 16 composites (i.e. combinations of proxies). Verbal intelligence was statistically significant in all models. Education was significant only in models with executive function as the cognitive outcome variable. Three robust composites were observed in more than two-thirds of brain-cognition models: the composites of (1) occupational complexity and verbal intelligence, (2) education and verbal intelligence, and (3) education, occupational complexity, and verbal intelligence. However, no composite had larger average effects nor was more robust than verbal intelligence alone.

CONCLUSION

These results support the use of verbal intelligence as a proxy measure of CR in cross-sectional studies of cognitively healthy older adults.

Reorganization of brain structural networks in aging: A longitudinal study

Normal aging is characterized by structural and functional changes in the brain contributing to cognitive decline. Structural connectivity (SC) describes the anatomical backbone linking distinct functional subunits of the brain and disruption of this communication is thought to be one of the potential contributors for the age-related deterioration observed in cognition. Several studies already explored brain network's reorganization during aging, but most focused on average connectivity of the whole-brain or in specific networks, such as the resting-state networks. Here, we aimed to characterize longitudinal changes of white matter (WM) structural brain networks, through the identification of sub-networks with significantly altered connectivity along time. Then, we tested associations between longitudinal changes in network connectivity and cognition. We also assessed longitudinal changes in topological properties of the networks. For this, older adults were evaluated at two timepoints, with a mean interval time of 52.8 months (SD = 7.24). WM structural networks were derived from diffusion magnetic resonance imaging, and cognitive status from neurocognitive testing. Our results show age-related changes in brain SC, characterized by both decreases and increases in connectivity weight. Interestingly, decreases occur in intra-hemispheric connections formed mainly by association fibers, while increases occur mostly in inter-hemispheric connections and involve association, commissural, and projection fibers, supporting the last-in-first-out hypothesis. Regarding topology, two hubs were lost, alongside with a decrease in connector-hub inter-modular connectivity, reflecting reduced integration. Simultaneously, there was an increase in the number of provincial hubs, suggesting increased segregation. Overall, these results confirm that aging triggers a reorganization of the brain structural network.

Gray matter volume in the right angular gyrus is associated with differential patterns of multisensory integration with aging

Multisensory perception might provide an important marker of brain function in aging. However, the cortical structures supporting multisensory perception in aging are poorly understood. In this study, we compared regional gray matter volume in a group of middle-aged (n = 101; 49-64 years) and older (n = 116; 71-87 years) adults from The Irish Longitudinal Study on Aging using voxel-based morphometry. Participants completed a measure of multisensory integration, the sound-induced flash illusion, and were grouped as per their illusion susceptibility. A significant interaction was observed in the right angular gyrus; in the middle-aged group, larger gray matter volume corresponded to stronger illusion perception while in older adults larger gray matter corresponded to less illusion susceptibility. This interaction remained significant even when controlling for a range of demographic, sensory, cognitive, and health variables. These findings show that multisensory integration is associated with specific structural differences in the aging brain and highlight the angular gyrus as a possible "cross-modal hub" associated with age-related change in multisensory perception.

Grey matter network trajectories across the Alzheimer's disease continuum and relation to cognition

Biomarkers are needed to monitor disease progression in Alzheimer's disease. Grey matter network measures have such potential, as they are related to amyloid aggregation in cognitively unimpaired individuals and to future cognitive decline in predementia Alzheimer's disease. Here, we investigated how grey matter network measures evolve over time within individuals across the entire Alzheimer's disease cognitive continuum and whether such changes relate to concurrent decline in cognition. We included 190 cognitively unimpaired, amyloid normal (controls) and 523 individuals with abnormal amyloid across the cognitive continuum (preclinical, prodromal, Alzheimer's disease dementia) from the Alzheimer's Disease Neuroimaging Initiative and calculated single-subject grey matter network measures (median of five networks per individual over 2 years). We fitted linear mixed models to investigate how network measures changed over time and whether such changes were associated with concurrent changes in memory, language, attention/executive functioning and on the Mini-Mental State Examination. We further assessed whether associations were modified by baseline disease stage. We found that both cognitive functioning and network measures declined over time, with steeper rates of decline in more advanced disease stages. In all cognitive stages, decline in network measures was associated with concurrent decline on the Mini-Mental State Examination, with stronger effects for individuals closer to Alzheimer's disease dementia. Decline in network measures was associated with concurrent cognitive decline in different cognitive domains depending on disease stage: In controls, decline in networks was associated with decline in memory and language functioning; preclinical Alzheimer's disease showed associations of decline in networks with memory and attention/executive functioning; prodromal Alzheimer's disease showed associations of decline in networks with cognitive decline in all domains; Alzheimer's disease dementia showed associations of decline in networks with attention/executive functioning. Decline in grey matter network measures over time accelerated for more advanced disease stages and was related to concurrent cognitive decline across the entire Alzheimer's disease cognitive continuum. These associations were disease stage dependent for the different cognitive domains, which reflected the respective cognitive stage. Our findings therefore suggest that grey matter measures are helpful to track disease progression in Alzheimer's disease.