White matter fibre density in the brain's inhibitory control network is associated with falling in low activity older adults.

Recent research has indicated that the relationship between age-related cognitive decline and falling may be mediated by the individual's capacity to quickly cancel or inhibit a motor response. This longitudinal investigation demonstrates that higher white matter fibre density in the motor inhibition network paired with low physical activity was associated with falling in elderly participants. We measured the density of white matter fibre tracts connecting key nodes in the inhibitory control network in a large sample (n = 414) of older adults. We modelled their self-reported frequency of falling over a 4-year period with white matter fibre density in pathways corresponding to the direct and hyperdirect cortical-subcortical loops implicated in the inhibitory control network. Only connectivity between right inferior frontal gyrus and right subthalamic nucleus was associated with falling as measured cross-sectionally. The connectivity was not, however, predictive of future falling when measured 2 and 4 years later. Higher white matter fibre density was associated with falling, but only in combination with low levels of physical activity. No such relationship existed for selected control brain regions that are not implicated in the inhibitory control network. Albeit statistically robust, the direction of this effect was counterintuitive (more dense connectivity associated with falling) and warrants further longitudinal investigation into whether white matter fibre density changes over time in a manner correlated with falling, and mediated by physical activity.

Mind versus body: Perceived stress and biological stress are independently related to cognitive decline.

Chronic stress may increase risk of age-related cognitive decline. 'Stress', however, is a multidimensional construct and few studies have investigated the inter-relationship of subjective stress and biological stress with cognitive decline. In this study, we examine the relationship between perceived stress and two measures of biological stress - allostatic load, indexing stress at the physiological level and leukocyte telomere length, indexing stress at the cellular level - with cognitive decline over a 12-year period in adults aged 50 and older. 3,458 participants (aged ≥ 50) from The Irish Longitudinal study on Ageing with measurements of allostatic load, telomere length and perceived stress at baseline and repeated measures of cognitive function were included. Hierarchical linear regression models with adjustment for multiple potential confounders were applied, and repeated stratified by sex in sensitivity analyses. Higher perceived stress at baseline was associated with lower cognitive function (ß = -0.10, 95 % CI -0.12, -0.07, p <.001), with similar strength of associations across waves. There were significant interactions between measures of biological stress and wave; higher allostatic load was associated (X2(18) = 64.4; p <.001), and telomere length was borderline (X2(18) = 9.4; p =.09) associated with cognitive decline from 4-year follow-up onward. Sex stratified analyses revealed that the association between telomere length and cognitive decline was present in women only. Mutual adjustment did not attenuate associations in either case. The interactions between allostatic load and telomere length with perceived stress were not significant. Our findings suggest that subjective measures of stress and biological metrics may be independently related to cognitive function over time in older adults, hinting at the potential for different underlying mechanisms.

Examining mental health and autonomic function as putative mediators of the relationship between sleep and trajectories of cognitive function: findings from the Irish longitudinal study on ageing (TILDA).

OBJECTIVES: This study investigates the mediating roles of autonomic function and mental health in the association between sleep and cognitive decline in adults aged 50 and above. METHOD: A total of 2,697 participants with observations on sleep and mediators at baseline and repeated measures of cognitive function (MMSE) were included. Clusters of individuals with similar cognitive trajectories (high-stable, mid-stable and low-declining) were identified. Multinomial logistic regressions were used to estimate the likelihood of membership to each trajectory group based on sleep duration and disturbance. Finally, mediation analysis tested potential mediating effects of autonomic function and mental health underpinning the sleep-cognition relationship. RESULTS: Short (p = .028), long (p =.019), and disturbed sleep (p =.008) increased the likelihood of a low-declining cognitive trajectory. Mental health measures fully attenuated relationships between cognitive decline and short or disturbed sleep but not long sleep. No autonomic function mediation was observed. CONCLUSION: Older adults with short or disturbed sleep are at risk of cognitive decline due to poor mental health. Individuals with long sleep are also at risk, however, the acting pathways remain to be identified. These outcomes have clinical implications, potentially identifying intervention strategies targeting mental health and sleep as prophylactic measures against dementia.

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.

The bi-directional association between loneliness and depression among older adults from before to during the COVID-19 pandemic.

BACKGROUND: Older adults have both the highest risk of contracting SARS-CoV-2 and in many jurisdictions have had additional restrictions placed on the social interactions. As a result, the COVID-19 pandemic has led to increased depression and loneliness among older adults. Using data from an established cohort of older adults, the aims of this study was to describe changes in loneliness and depression and to examine the directionality of the association between depression and loneliness over a 5-year period that included the early months of the pandemic. METHODS: Data were from The Irish Longitudinal Study on Ageing (TILDA), a large cohort of community-dwelling adults aged 54+. We applied an auto-regressive cross-lagged panel modelling approach to estimate the effect of depression on loneliness and vice versa over three time points. RESULTS: Both depression and loneliness increased significantly in the early months of the pandemic. While the association between loneliness and depression was bi-directional, loneliness was a stronger predictor of depression. CONCLUSION: The strength and bi-directionality of the association between loneliness and depression suggests that interventions to alleviate loneliness may also help reduce depressive symptoms and vice versa.

Assessing cognitive function in longitudinal studies of ageing worldwide: some practical considerations.

Over 55 million people live with dementia worldwide. With 40% of modifiable risk factors estimated to contribute to dementia, the potential for prevention is high, and preventive measures, at an early stage of cognitive decline, are likely to positively influence future dementia trends. Countries need reliable health data and adequate measurement tools to quantify, monitor and track early changes in cognitive capacity in the general population. Many cognitive tests exist; however, there is no consensus to date about which instruments should be employed, and important variations in measurement have been observed. In this narrative review, we present a number of cognitive tests that have been used in nationally representative population-based longitudinal studies of ageing. Longitudinal panel studies of ageing represent critical platforms towards capturing the process of cognitive ageing and understanding associated risk and protective factors. We highlight optimal measures for use at a population level and for cross-country comparisons, taking into consideration instrument reliability, validity, duration, ease of administration, costs, literacy and numeracy requirements, adaptability to sensory and fine motor impairments and portability to different cultural and linguistic milieux. Drawing upon the strengths and limitations of each of these tests, and the experience gained and lessons learnt from conducting a nationally representative study of ageing, we indicate a comprehensive battery of tests for the assessment of cognitive capacity, designed to facilitate its standardised operationalisation worldwide.

Do Mini-Mental State Examination and Montreal Cognitive Assessment predict high-cost health care users? A competing risks analysis in The Irish Longitudinal Study on Ageing.

OBJECTIVES: Policymakers want to better identify in advance the 10% of people who account for approximately 75% of health care costs. We evaluated how well Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) predicted high costs in Ireland. METHODS/DESIGN: We used five waves from The Irish Longitudinal Study on Ageing, a biennial population-representative survey of people aged 50+ (2010-2018). We used competing risks analysis where our outcome of interest was "high costs" (top 10% at any wave) and the competing outcome was dying or loss to follow-up without first having the high-cost outcome. Our binary predictors of interest were a 'low score' (bottom 10% in the sample) in MMSE (≤25 pts) and MoCA (≤19 pts) at baseline, and we calculated sub-hazard ratios after controlling for sociodemographic, clinical and functional factors. RESULTS: Of 5856 participants, 1427 (24%) had the 'high cost' outcome; 1463 (25%) had a competing outcome; and 2966 (51%) completed eight years of follow-up without either outcome. In multivariable regressions a low MoCA score was associated with high costs (SHR: 1.38 (95% CI: 1.2-1.6) but a low MMSE score was not. Low MoCA score at baseline had a higher true positive rate (40%) than did low MMSE score (35%). The scores had similar association with exit from the study. CONCLUSIONS: MoCA had superior predictive accuracy for high costs than MMSE but the two scores identify somewhat different types of high-cost user. Combining the approaches may improve efforts to identify in advance high-cost users.

StrokeCog Markov Model: Projected Prevalent and Incident Cases of Stroke and Poststroke Cognitive Impairment to 2035 in Ireland.

BACKGROUND AND PURPOSE: Cognitive impairment no dementia (CIND) and dementia are common stroke outcomes, with significant health and societal implications for aging populations. These outcomes are not included in current epidemiological models. We aimed to develop an epidemiological model to project incidence and prevalence of stroke, poststroke CIND and dementia, and life expectancy, in Ireland to 2035, informing policy and service planning. METHODS: We developed a probabilistic Markov model (the StrokeCog model) applied to the Irish population aged 40 to 89 years to 2035. Data sources included official population and hospital-episode statistics, longitudinal cohort studies, and published estimates. Key assumptions were varied in sensitivity analysis. Results were externally validated against independent sources. The model tracks poststroke progression into health states characterized by no cognitive impairment, CIND, dementia, disability, stroke recurrence, and death. RESULTS: We projected 69 051 people with prevalent stroke in Ireland in 2035 (22.0 per 1000 population [95% CI, 20.8-23.1]), with 25 274 (8.0 per 1000 population [95% CI, 7.1-9.0]) of those projected to have poststroke CIND, and 12 442 having poststroke dementia (4.0 per 1000 population [95% CI, 3.2-4.8]). We projected 8725 annual incident strokes in 2035 (2.8 per 1000 population [95% CI, 2.7-2.9]), with 3832 of these having CIND (1.2 per 1000 population [95% CI, 1.1-1.3]), and 1715 with dementia (0.5 per 1000 population [95% CI, 0.5-0.6]). Life expectancy for stroke survivors at age 50 was 23.4 years (95% CI, 22.3-24.5) for women and 20.7 (95% CI, 19.5-21.9) for men. CONCLUSIONS: This novel epidemiological model of stroke, poststroke CIND, and dementia draws on the best available evidence. Sensitivity analysis indicated that findings were robust to assumptions, and where there was uncertainty a conservative approach was taken. The StrokeCog model is a useful tool for service planning and cost-effectiveness analysis and is available for adaptation to other national contexts.

Associations between cognitive function, actigraphy-based and self-reported sleep in older community-dwelling adults: Findings from the Irish Longitudinal Study on Ageing.

OBJECTIVE: Cognitive impairment is prevalent in older ages. Associations with sleep are well established; however, ambiguity remains in which sleep characteristics contribute to this impairment. We examined cross-sectional associations between both self-reported and actigraphy-based sleep and cognitive performance across a number of domains in community-dwelling older adults. METHODS: 1520 participants aged 50 and older with self-reported and actigraphy-based total sleep time (TST) (≤5, 6, 7-8, 9 and ≥10 h) and self-reported sleep problems were analysed. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), verbal fluency, immediate and delayed recall memory, colour trails tests, and choice reaction tests (CRT). Associations between sleep and cognition were modelled using linear and negative binomial regression. RESULTS: Negative associations were found between ≥10 h of self-reported TST and MoCA error rate (incidence rate ratio [IRR] = 1.42; 95% confidence interval [CI] = 1.18, 1.71; p < 0.001); verbal fluency (beta [B] = -2.32 words; 95% CI = -4.00, -0.65; p < 0.01); and delayed recall (B = -0.91 words; 95% CI = -1.58, -0.25; p < 0.05) compared to 7-8 h. Significant associations with actigraphy-based TST were limited to MoCA error rate in ≤5 h (IRR = 1.22; 95% CI = 1.02, 1.45; p < 0.05) compared to 7-8 h. Higher numbers of sleep problems were associated with slower performance in CRT cognitive response time (IRR = 1.02; 95% CI = 1.00, 104; p < 0.05) and total response time (IRR = 1.02; 95% CI = 1.00, 1.04; p < 0.05). CONCLUSIONS: Self-reported long sleep duration was consistently associated with worse cognitive performance across multiple domains. Marginal associations between cognition and both actigraphy-based sleep and self-reported sleep problems were also apparent. These results further affirm poor sleep as a risk factor for cognitive impairment.

Associations between Cardiovascular Signal Entropy and Cognitive Performance over Eight Years.

In this study, the relationship between non-invasively measured cardiovascular signal entropy and global cognitive performance was explored in a sample of community-dwelling older adults from The Irish Longitudinal Study on Ageing (TILDA), both cross-sectionally at baseline (n = 4525; mean (SD) age: 61.9 (8.4) years; 54.1% female) and longitudinally. We hypothesised that signal disorder in the cardiovascular system, as quantified by short-length signal entropy during rest, could provide a marker for cognitive function. Global cognitive function was assessed via Mini Mental State Examination (MMSE) across five longitudinal waves (8 year period; n = 4316; mean (SD) age: 61.9 (8.4) years; 54.4% female) and the Montreal Cognitive Assessment (MOCA) across two longitudinal waves (4 year period; n = 3600; mean (SD) age: 61.7 (8.2) years; 54.1% female). Blood pressure (BP) was continuously monitored during supine rest at baseline, and sample entropy values were calculated for one-minute and five-minute sections of this data, both for time-series data interpolated at 5 Hz and beat-to-beat data. Results revealed significant associations between BP signal entropy and cognitive performance, both cross-sectionally and longitudinally. Results also suggested that as regards associations with cognitive performance, the entropy analysis approach used herein potentially outperformed more traditional cardiovascular measures such as resting heart rate and heart rate variability. The quantification of entropy in short-length BP signals could provide a clinically useful marker of the cardiovascular dysregulations that potentially underlie cognitive decline.

Impaired orthostatic heart rate recovery is associated with smaller thalamic volume: Results from The Irish Longitudinal Study on Aging (TILDA).

The thalamus is a central hub of the autonomic network and thalamic volume has been associated with high-risk phenotypes for sudden cardiac death. Heart rate response to physiological stressors (e.g., standing) and the associated recovery patterns provide reliable indicators of both autonomic function and cardiovascular risk. Here we examine if thalamic volume may be a risk marker for impaired heart rate recovery in response to orthostatic challenge. The Irish Longitudinal Study on Aging involves a nationally representative sample of older individuals aged ≥50 years. Multimodal brain magnetic resonance imaging and orthostatic heart rate recovery were available for a cross-sectional sample of 430 participants. Multivariable regression and linear mixed-effects models were adjusted for head size, age, sex, education, body mass index, blood pressure, history of cardiovascular diseases and events, cardiovascular medication, diabetes mellitus, smoking, alcohol intake, timed up-and-go (a measure of physical frailty), physical exercise and depression. Smaller thalamic volume was associated with slower heart rate recovery (-1.4 bpm per 1 cm3 thalamic volume, 95% CI -2.01 to -0.82; p < .001). In multivariable analysis, participants with smaller thalamic volumes had a mean heart rate recovery -2.7 bpm slower than participants with larger thalamic volumes (95% CI -3.89 to -1.61; p < .001). Covariates associated with smaller thalamic volume included age, history of diabetes, and heavy alcohol consumption. Thalamic volume may be an indicator of the structural integrity of the central autonomic network. It may be a clinical biomarker for stratification of individuals at risk of autonomic dysfunction, cardiovascular events, and sudden cardiac death.

Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.

INTRODUCTION: Machine learning methods have been introduced as a computer aided diagnostic tool, with applications to glioma characterisation on MRI. Such an algorithmic approach may provide a useful adjunct for a rapid and accurate diagnosis of a glioma. The aim of this study is to devise a machine learning algorithm that may be used by radiologists in routine practice to aid diagnosis of both: WHO grade and IDH mutation status in de novo gliomas. METHODS: To evaluate the status quo, we interrogated the accuracy of neuroradiology reports in relation to WHO grade: grade II 96.49% (95% confidence intervals [CI] 0.88, 0.99); III 36.51% (95% CI 0.24, 0.50); IV 72.9% (95% CI 0.67, 0.78). We derived five MRI parameters from the same diagnostic brain scans, in under two minutes per case, and then supplied these data to a random forest algorithm. RESULTS: Machine learning resulted in a high level of accuracy in prediction of tumour grade: grade II/III; area under the receiver operating characteristic curve (AUC) = 98%, sensitivity = 0.82, specificity = 0.94; grade II/IV; AUC = 100%, sensitivity = 1.0, specificity = 1.0; grade III/IV; AUC = 97%, sensitivity = 0.83, specificity = 0.97. Furthermore, machine learning also facilitated the discrimination of IDH status: AUC of 88%, sensitivity = 0.81, specificity = 0.77. CONCLUSIONS: These data demonstrate the ability of machine learning to accurately classify diffuse gliomas by both WHO grade and IDH status from routine MRI alone-without significant image processing, which may facilitate usage as a diagnostic adjunct in clinical practice.

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 (ß = -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.

Examining the Impact of Socioeconomic Position Across the Life Course on Cognitive Function and Brain Structure in Healthy Aging.

This study explores the relationship of life-course intergenerational social mobility with cognitive function and brain structure in older adults using Diagonal Reference Models. Data from the Irish Longitudinal Study on Ageing, a population-based cohort of adults aged 50 years and older (N = 4 620 participants; mean age: 66.1; standard deviation: 9.1; 55% female) was used for analysis. Brain magnetic resonance imaging data were available for 464 participants. Social mobility was characterized as the difference between childhood socioeconomic position (SEP; ie, father's occupation) and adulthood SEP (ie, own occupation). The Montreal Cognitive Assessment (MoCA), the Mini-Mental State Examination (MMSE), cortical thickness, and total gray matter volume (GMV) served as global cognitive and brain measures. Exploratory analyses included the volumes of the ventromedial prefrontal cortex (vmPFC), anterior cingulate (AC), hippocampus, and amygdala. A social gradient in cognitive function was observed among the intergenerationally stable; brain structure was not as clearly socially patterned. Adulthood SEP was significantly associated with MoCA (weight = 0.76; p < .001), MMSE (weight = 0.91; p < .001), GMV (weight = 0.77; p = .002), and AC volume (weight = 0.76; p < .001), whereas childhood SEP was associated with vmPFC volume (weight = 1.00; p = .003). There was no independent association of social mobility with any of the outcomes. Together our results suggest that both childhood and adulthood SEP are important in shaping later-life brain health, but that adulthood SEP predominates in terms of its influence. This is potentially an important insight as it suggests that brain health may be modifiable if socioeconomic circumstances change.

Relationship between hippocampal subfield volumes and cognitive decline in healthy subjects.

We examined the relationship between hippocampal subfield volumes and cognitive decline over a 4-year period in a healthy older adult population with the goal of identifying subjects at risk of progressive cognitive impairment which could potentially guide therapeutic interventions and monitoring. 482 subjects (68.1 years +/- 7.4; 52.9% female) from the Irish Longitudinal Study on Ageing underwent magnetic resonance brain imaging and a series of cognitive tests. Using K-means longitudinal clustering, subjects were first grouped into three separate global and domain-specific cognitive function trajectories; High-Stable, Mid-Stable and Low-Declining. Linear mixed effects models were then used to establish associations between hippocampal subfield volumes and cognitive groups. Decline in multiple hippocampal subfields was associated with global cognitive decline, specifically the presubiculum (estimate -0.20; 95% confidence interval (CI) -0.78 - -0.02; p = 0.03), subiculum (-0.44; -0.82 - -0.06; p = 0.02), CA1 (-0.34; -0.78 - -0.02; p = 0.04), CA4 (-0.55; -0.93 - -0.17; p = 0.005), molecular layer (-0.49; -0.87 - -0.11; p = 0.01), dentate gyrus (-0.57; -0.94 - -0.19; p = 0.003), hippocampal tail (-0.53; -0.91 - -0.15; p = 0.006) and HATA (-0.41; -0.79 - -0.03; p = 0.04), with smaller volumes for the Low-Declining cognition group compared to the High-Stable cognition group. In contrast to global cognitive decline, when specifically assessing the memory domain, cornu ammonis 1 subfield was not found to be associated with low declining cognition (-0.14; -0.37 - 0.10; p = 0.26). Previously published data shows that atrophy of specific hippocampal subfields is associated with cognitive decline but our study confirms the same effect in subjects asymptomatic at time of enrolment. This strengthens the predictive value of hippocampal subfield atrophy in risk of cognitive decline and may provide a biomarker for monitoring treatment efficacy.

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 ß=323.0mm3 (95% Confidence Interval [CI] 84.5, 561.6) and when comparing participants with ≥20 teeth to edentates there was an increase of ß=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 ß=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.

Word finding, prosody and social cognition in multiple sclerosis.

BACKGROUND: Impairments in speech and social cognition have been reported in people with multiple sclerosis (pwMS), although their relationships with neuropsychological outcomes and their clinical utility in MS are unclear. OBJECTIVES: To evaluate word finding, prosody and social cognition in pwMS relative to healthy controls (HC). METHODS: We recruited people with relapsing MS (RMS, n = 21), progressive MS (PMS, n = 24) and HC (n = 25) from an outpatient MS clinic. Participants completed a battery of word-finding, social cognitive, neuropsychological and clinical assessments and performed a speech task for prosodic analysis. RESULTS: Of 45 pwMS, mean (SD) age was 49.4 (9.4) years, and median (range) Expanded Disability Severity Scale score was 3.5 (1.0-6.5). Compared with HC, pwMS were older and had slower information processing speed (measured with the Symbol Digit Modalities Test, SDMT) and higher depression scores. Most speech and social cognitive measures were associated with information processing speed but not with depression. Unlike speech, social cognition consistently correlated with intelligence and memory. Visual naming test mean response time (VNT-MRT) demonstrated worse outcomes in MS versus HC (p = .034, Nagelkerke's R2  = 65.0%), and in PMS versus RMS (p = .009, Nagelkerke's R2  = 50.2%). Rapid automatised object naming demonstrated worse outcomes in MS versus HC (p = .014, Nagelkerke's R2  = 49.1%). These word-finding measures showed larger effect sizes than that of the SDMT (MS vs. HC, p = .010, Nagelkerke's R2  = 40.6%; PMS vs. RMS, p = .023, Nagelkerke's R2  = 43.5%). Prosody and social cognition did not differ between MS and HC. CONCLUSIONS: Word finding, prosody and social cognition in MS are associated with information processing speed and largely independent of mood. Impairment in visual object meaning perception is potentially a unique MS disease-related deficit that could be further explored and cautiously considered as an adjunct disability metric for MS.

Structural brain signatures of frailty, defined as accumulation of self-reported health deficits in older adults.

Background: Frailty in older adults has been associated with reduced brain health. However, structural brain signatures of frailty remain understudied. Our aims were: (1) Explore associations between a frailty index (FI) and brain structure on magnetic resonance imaging (MRI). (2) Identify the most important FI features driving the associations. Methods: We designed a cross-sectional observational study from a population-based study (The Irish Longitudinal Study on Aging: TILDA). Participants aged ≥50 years who underwent the wave 3 MRI sub-study were included. We measured cortex, basal ganglia, and each of the Desikan-Killiany regional volumes. Age-and sex-adjusted correlations were performed with a 32-item self-reported FI that included conditions commonly tested for frailty in research and clinical settings. A graph theory analysis of the network composed by each FI item and cortex volume was performed. White matter fiber integrity was quantified using diffusion tensor imaging (DTI). Results: In 523 participants (mean age 69, 49% men), lower cortex and thalamic volumes were independently associated with higher FI. Sensory and functional difficulties, diabetes, polypharmacy, knee pain, and self-reported health were the main FI associations with cortex volume. In the network analysis, cortex volume had a modest influence within the frailty network. Regionally, higher FI was significantly associated with lower volumes in both orbitofrontal and temporal cortices. DTI analyses revealed inverse associations between the FI and the integrity of some association bundles. Conclusion: The FI used had a recognizable but subtle structural brain signature in this sample. Only some FI deficits were directly associated with cortex volume, suggesting scope for developing FIs that include metrics more specifically related with brain health in future aging neuroscience studies.

Brain connectivity in frailty: Insights from The Irish Longitudinal Study on Ageing (TILDA).

Frailty in older adults is associated with greater risk of cognitive decline. Brain connectivity insights could help understand the association, but studies are lacking. We applied connectome-based predictive modeling to a 32-item self-reported Frailty Index (FI) using resting state functional MRI data from The Irish Longitudinal Study on Ageing. A total of 347 participants were included (48.9% male, mean age 68.2 years). From connectome-based predictive modeling, we obtained 204 edges that positively correlated with the FI and composed the "frailty network" characterised by connectivity of the visual network (right); and 188 edges that negatively correlated with the FI and formed the "robustness network" characterized by connectivity in the basal ganglia. Both networks' highest degree node was the caudate but with different patterns: from caudate to visual network in the frailty network; and to default mode network in the robustness network. The FI was correlated with walking speed but not with metrics of global cognition, reinforcing the matching between the FI and the brain connectivity pattern found (main predicted connectivity in basal ganglia).

Tooth loss and cognitive decline in community dwelling older Irish adults: A cross-sectional cohort study.

OBJECTIVES: To investigate whether tooth loss and related loss of occluding tooth pairs, were associated with cognitive decline in a group of community dwelling older men and women from Ireland. METHODS: A group of 2508 men and women, aged 50-93 years, underwent a dental examination as part of The Irish Longitudinal Study of ageing (TILDA). Global cognitive function was assessed using the mini-mental state examination (MMSE). Analysis included multiple logistic regression with adjustment for various confounders. RESULTS: The mean age of participants was 65.5 years (SD 8.1) and 55.3% of the group were female. Three hundred and twenty-nine (13.1%) of the cohort were classified as having a low MMSE with a score ≤ 27. After adjustment for confounding variables, compared to subjects with ≥ 20 teeth, the odds ratio for a low MMSE amongst edentulous was 1.55 (95% CI 1.03-2.34) p = 0.03, and for those with 1-19 teeth was 1.38 (95% CI 1.03-1.84) p = 0.04. Having < 10 natural occluding pairs and < 4 posterior occluding pairs also associated with a low MMSE. CONCLUSIONS: In this cross-sectional cohort study, tooth loss and related loss of occluding tooth pairs were associated with a low MMSE in a group of older adults from Ireland, independent of various known confounders. CLINICAL SIGNIFICANCE: Dentists should be aware of the potential systemic health implications of patients presenting with tooth loss. Tooth loss may be an important risk indicator for cognitive decline.