Global Measures Research Articles

Graph Theory Analysis of Structural Connectivity in Limbic‐predominant Age‐related TDP‐43 Encephalopathy Neuropathological Change (LATE‐NC)

AbstractBackgroundThe anatomical distribution of limbic‐predominant age‐related TDP‐43 encephalopathy neuropathological change (LATE‐NC) typically involves the amygdala, hippocampus, and other subcortical, temporal and frontal lobe regions. But its impact on the structural integrity of this network of regions remains unknown. In this study, we tested the hypothesis that LATE‐NC is associated with abnormalities in graph theoretic measures of structural connectivity in the network of regions known to be involved in LATE‐NC.MethodThis study included 148 deceased older adults participating in Rush Memory and Aging Project and Religious Orders Study (Fig.1A). Ex‐vivo diffusion tensor imaging (DTI) scans were acquired on 3T scanners, followed by detailed neuropathologic examination by a board‐certified neuropathologist (Fig.1B). Fractional anisotropy (FA) maps derived from DTI scans were used to define region‐to‐region structural connectivity in a network of 19 regions known to be involved in LATE‐NC using graph theory‐based network measures (Fig.2).General linear models were used to investigate the association of global and local graph measures with LATE‐NC stages, controlling for other neuropathologies (Alzheimer’s disease, Lewy bodies, arteriolosclerosis, atherosclerosis, cerebral amyloid angiopathy, gross and microscopic infarcts), demographics (age at death, sex, education), total white matter hyperintensity volume, postmortem intervals and scanner variables. Statistical significance was set at p<0.05.ResultLinear regression revealed that greater LATE‐NC stage was associated with increased characteristic path length and with lower values of the remaining global network measures (p<0.05) (Fig.3A). LATE‐NC was also associated with lower local efficiency, increased path length, lower nodal strength, and lower clustering coefficient in 74%, 79%, 32%, and 63% of the nodes, respectively (p<0.05) (Fig.3B). Finally, LATE‐NC was associated with both greater (in 21% of nodes) and lower (in 16% of nodes) eigenvector centrality, and with both greater and lower betweenness centrality in 21% of nodes, respectively (p<0.05) (Fig.3B).ConclusionUsing graph theory and a hypothesis‐driven approach, we found significant degradation of structural integrity in white matter of the network of regions affected by LATE‐NC. These findings may shed light on the effects of LATE‐NC on brain connectivity, and in combination with other imaging and clinical information, may aid towards the development of tools for in‐vivo detection of this devastating neuropathology.

Genetic Drivers of Atypical Alzheimer’s Disease Neuropathologic Change

AbstractBackgroundQuantitative differences in neurofibrillary tangle density are not well captured by more global measures such as Braak staging. Indeed, amongst cases with high Alzheimer’s disease neuropathologic change (ADNC), quantitative differences in the distribution of neurofibrillary tangle density is associated with atypical, non‐amnestic clinical presentations. We sought here to study the effect of TREM2 and APOE risk genotypes on neuropathologically and clinically defined atypical Alzheimer’s disease.MethodsTREM2 variant versus wild‐type autopsy cases with an intermediate to high level of ADNC were identified from the Center for Neurodegenerative Disease Research Brain Bank at the University of Pennsylvania. Archived clinical records were used to classify cases into typical versus atypical AD. Neuropathologic classification of cases into typical versus atypical AD was based on quantification of neurofibrillary tangle density using PHF1 stained sections from neocortical and hippocampal regions. Morphology from Iba1 stained sections was used to quantify microglial reactivity.Results31 AD cases with TREM2 risk genotypes were compared to wild‐type TREM2 AD cases (n = 119). TREM2 variants were associated with a significantly higher proportion of atypical AD clinical phenotypes including behavioral/dysexecutive variants, primary progressive aphasias, posterior cortical atrophy, and others (19.33% versus 48.39%, Fisher’s exact test p = 0.002). These clinical phenotypes were associated with a significantly higher proportion of TREM2 variant cases with neuropathologically defined atypical AD, namely hippocampal sparing AD (8.7% versus 28.57%, Fisher’s exact test p = 0.046). Moreover, the proportion of microglia with a dystrophic morphology correlated with neurofibrillary tangle density and not amyloid burden. Finally, to get a sense of the magnitude of this TREM2 association relative to other genetic risk factors, we observed a non‐significant trend towards the absence of the APOE E4 risk genotype being associated with hippocampal sparing AD.ConclusionsThis clinicopathologic correlation study suggests that TREM2 risk variants are associated with clinically and neuropathologically defined atypical AD. Given that both TREM2 and APOE affect microglial reactivity to amyloid, the observed tendency towards TREM2 variant cases exhibiting hippocampal sparing AD suggests that altered microglial reactivity to amyloid may change downstream tauopathy patterns leading to atypical AD clinical phenotypes.

Altered resting state hippocampal connectivity associated with amyloid and tau in older adults without dementia from a population‐based cohort study

AbstractBackgroundAlzheimer’s disease (AD) is characterized by amyloid beta plaques and tau‐containing neurofibrillary tangles with disrupted (high and low) resting state hippocampal connectivity. One potential factor that may underlie these differences is that early stages of disease may contribute to greater connectivity and later stages may contribute to lower connectivity (i.e., quadratic associations between amyloid/tau and connectivity). Early stages may be associated with greater recruitment of intranetwork connectivity to compensate, which fails at later stages. Late stages may be associated with greater recruitment of internetwork connectivity, that fails in advanced cognitive impairment. Understanding these dynamics may help us understand resilience to amyloid and tau in cognitively unimpaired individuals.MethodWe recruited 115 adults >65 years old (67‐96, mean 76years) from a population‐based study into a neuroimaging sub‐study. The study area is a formerly heavy manufacturing industrial small‐town area. Participants (106 (92%) CU with CDR = 0) underwent PET imaging for amyloid (PiB) and tau (AV‐1451) and global SUVR measures were computed after appropriate preprocessing. Participants underwent resting state fMRI and hippocampal connectivity was computed for the left/right and anterior/posterior hippocampus. Regression analyses between connectivity and both linear and quadratic terms for amyloid and tau were adjusted for age, sex, race, and education. We adjusted for multiple comparisons using SnPM with FWE correction with α = 0.05 (p‐value threshold of 0.001).ResultWe found a negative quadratic association between left anterior hippocampus with default mode network (DMN) including the posterior cingulate and supramarginal gyrus, where greater amyloid and lower amyloid was associated with low connectivity. Similar effects were found for the right anterior hippocampus. Right anterior hippocampus to cuneus connectivity shows positive U‐shape with amyloid but negative linear relationship with tau. Greater right anterior hippocampus‐inferior parietal and right posterior hippocampus‐inferior temporal connectivity was associated with greater tau. Left posterior hippocampus to left middle temporal showed negative U‐shape with tau.ConclusionAmyloid and tau showed complex inverse U‐shaped associations between heightened intranetwork connectivity and moderate amyloid/tau, but low connectivity with higher severity. Internetwork connectivity was heightened with greater tau. These may reflect altered connectivity due to changes in amyloid and tau in older adults without dementia.

Cerebellar‐cortical functional connectivity is associated with Alzheimer’s disease pathology and cerebellar atrophy

AbstractBackgroundBrain atrophy has been associated with Alzheimer’s disease (AD) pathology. Previous research also suggests that functional connectivity (FC) among distributed neural networks is disrupted in preclinical AD. The cerebellum has been thought to play a crucial role in motor control, yet recent evidence points to its additional role in non‐motor domains as well as cognitive decline in AD. Cerebellar volume has been shown to decline along the course of AD progression. Moreover, neuroimaging studies have delineated intrinsic cerebellar‐cortical functional networks that presumably support cognitive functions. Despite the accumulating findings on neurodegeneration or FC, how cerebellar FC and atrophy relate to AD pathology in the early stage has not been extensively investigated.MethodData from 83 cognitively normal older adults (mean 71.0 yrs, 66% females) in the Alzheimer’s Disease Neuroimaging Initiative were analyzed. Volumetric data were obtained from FreeSurfer 6.0 segmentation. Resting state fMRI scans were preprocessed using the CONN Toolbox. Aß and tau standardized uptake value ratio (SUVR) data were obtained from [18F]‐Florbetapir or [18F]‐Florbetaben (Aß) and [18F]‐Flortaucipir (tau) PET scans. For Aß, SUVR values were transformed to the Centiloid scale, and a global summary measure was used. For tau, SUVR values in the temporal meta regions of interest were used. Seed‐based functional connectivity metrics were computed using the 7 cerebellar parcellations (Buckner et al., 2011) that are functionally coupled to different cortical networks (Yeo et al., 2011).ResultCerebellar volume showed no significant relationship with amyloid or tau SUVR. By contrast, hippocampal atrophy was positively associated with amyloid or tau SUVR and showed trending significance (ps < 0.1). Increased Aß burden was associated with increased cerebellar‐cortical FC in the attention, frontoparietal, and default mode networks. Increased tau load was associated with increased cerebellar‐cortical FC in the visual, somatomotor, and attention networks. Cerebellar volume was associated with cerebellar‐cortical FC in the visual, somatomotor, attention networks, but not with the limbic, frontoparietal, or default mode networks.ConclusionOur findings suggest that functional cerebellar‐cortical connectivity varies with amyloid and tau pathology in different networks, and such functional changes may precede cerebellar atrophy in preclinical AD.

Versatile MRI acquisition and processing protocol for population‐based neuroimaging

AbstractBackgroundNeuroimaging plays an essential role in epidemiological studies and a special focus is directed towards the employment of versatile MRI acquisition and processing. The proposed multi‐purpose MRI protocol was designed for large‐scale and long‐term population neuroimaging and includes structural, diffusion‐weighted, and functional MRI modalities. It directly links the acquisition of an extensive set of MRI contrasts with fully automated data processing pipelines and quality assurance of the MRI data and image‐derived phenotypes.MethodThe MRI acquisition protocol is largely based on in‐house developed MR sequences. With a total scan time below one hour per participant, it allows to acquire multiple MR contrasts at 3T with whole‐brain coverage and high isotropic image resolution, while keeping potential subject discomfort and motion artifacts at manageable levels. Designed to be kept constant, but also adaptive, the scan protocol separates into a core imaging protocol with MR contrasts of high relevance acquired for all study participants, and a free protocol to accommodate alternative promising MRI techniques in smaller sub‐populations. The analysis protocol handles large‐scale imaging data by means of fast and fully automated processing pipelines that incorporate state‐of‐the‐art image analysis tools and innovative machine learning methods, particularly using deep learning. Dedicated quality assessment (QA) includes visual rating and inspection for incidental findings on structural MRI and QA workflows tailored for each postprocessing pipeline to automatically identify problematic data based on the distribution of subject‐specific QA metrics with respect to the population average.ResultThe MRI protocol has been successfully applied in the Rhineland Study, a prospective cohort study in Bonn, Germany, with currently over 10,000 participants. Image‐derived phenotypes include: global and regional brain tissue volume, thickness and surface measures from multi‐modal structural MRI, global and regional microstructural measures based on diffusion‐weighted MRI, brain functional connectivity using resting‐state functional MRI, and volumes of subcutaneous and visceral adipose tissue based on a single‐breathhold abdominal MRI (Figure 1).ConclusionWe present a versatile MRI protocol with acquisition and analysis methods that are generally applicable and not geared towards a specific disease or research question. Thus, this protocol may be of specific interest for many neuroimaging applications including population imaging studies.

Functional connectivity in Alzheimer’s disease: A resting‐state EEG study

AbstractBackgroundAlzheimer’s disease (AD) is mainly associated with amnestic deficits. Imaging studies revealed a disruption of functional networks in AD, which plays a crucial role for the cognitive deficits. There is also evidence from resting‐state Electroencephalography (rsEEG) studies, which found altered functional connectivity measuring EEG coherence in AD (Babiloni et al., 2021; Wang et al., 2015). This was especially seen for the Alpha frequency band, which is known for its diagnostic potential in the disease. Furthermore, studies suggest that Alpha band marker correlate with cognitive decline in AD (Babiloni et al., 2010). The main aim of the current work is to gain a better understanding of the functional connectivity in Alzheimer’s disease based on EEG given a very high temporal resolution.MethodThe sample consisted of 15 patients (AD, 72.3 ± 8.28 years, 66.7% male) with mild cognitive impairment to mild dementia with a typical cerebrospinal fluid profile of Alzheimer’s disease or pathological Amyloid‐PET and 15 age‐matched healthy controls (HC, 72.93 ± 7.17 years, 53.3% male). All participants underwent a neuropsychological examination and rsEEG. The rsEEG was recorded with the Neurowerk Amplifier using an elastic cap with 19 electrodes (10‐20 system). Raw data were preprocessed and further analyzed with regard to functional connectivity focusing on the Alpha frequency band (Brainstorm, SPSS, EEGlab). Functional connectivity was calculated by the magnitude squared coherence. Coherence was further clustered in global coherence and coherence per electrode. Finally, coherence scores were evaluated in relation to neuropsychological scores.ResultsCenters of functional connectivity were found in frontal‐frontal and frontal‐parietal/occipital electrode pairs. Alpha frequency band (8 – 13 Hz), particularly Alpha1 frequency band (8 – 11 Hz), yielded the highest coherence scores. When comparing AD and HC, patients showed reduced coherence in Alpha2 (11 – 13 Hz) and Beta (13 – 20 Hz). Additionally, moderate correlations of global coherence and behavioral measures were found mainly for the Alpha1 frequency band.ConclusionAlzheimer’s disease can be associated with poorer functional connections of certain brain areas and rsEEG coherence might be a potential biomarker for AD.

Cerebellar‐cortical functional connectivity is associated with Alzheimer’s disease pathology and cerebellar atrophy

AbstractBackgroundBrain atrophy has been associated with Alzheimer’s disease (AD) pathology. Previous research also suggests that functional connectivity (FC) among distributed neural networks is disrupted in preclinical AD. The cerebellum has been thought to play a crucial role in motor control, yet recent evidence points to its additional role in non‐motor domains as well as cognitive decline in AD. Cerebellar volume has been shown to decline along the course of AD progression. Moreover, neuroimaging studies have delineated intrinsic cerebellar‐cortical functional networks that presumably support cognitive functions. Despite the accumulating findings on neurodegeneration or FC, how cerebellar FC and atrophy relate to AD pathology in the early stage has not been extensively investigated.MethodData from 83 cognitively normal older adults (mean 71.0 yrs, 66% females) in the Alzheimer’s Disease Neuroimaging Initiative were analyzed. Volumetric data were obtained from FreeSurfer 6.0 segmentation. Resting state fMRI scans were preprocessed using the CONN Toolbox. Aβ and tau standardized uptake value ratio (SUVR) data were obtained from [18F]‐Florbetapir or [18F]‐Florbetaben (Aβ) and [18F]‐Flortaucipir (tau) PET scans. For Aβ, SUVR values were transformed to the Centiloid scale, and a global summary measure was used. For tau, SUVR values in the temporal meta regions of interest were used. Seed‐based functional connectivity metrics were computed using the 7 cerebellar parcellations (Buckner et al., 2011) that are functionally coupled to different cortical networks (Yeo et al., 2011).ResultCerebellar volume showed no significant relationship with amyloid or tau SUVR. By contrast, hippocampal atrophy was positively associated with amyloid or tau SUVR and showed trending significance (ps < 0.1). Increased Aβ burden was associated with increased cerebellar‐cortical FC in the attention, frontoparietal, and default mode networks. Increased tau load was associated with increased cerebellar‐cortical FC in the visual, somatomotor, and attention networks. Cerebellar volume was associated with cerebellar‐cortical FC in the visual, somatomotor, attention networks, but not with the limbic, frontoparietal, or default mode networks.ConclusionOur findings suggest that functional cerebellar‐cortical connectivity varies with amyloid and tau pathology in different networks, and such functional changes may precede cerebellar atrophy in preclinical AD.

Alzheimer’s disease is associated with increased modularity and assortativity: Evidence from structural and metabolic connectivity

AbstractBackgroundAlzheimer’s disease (AD) is a progressive disorder associated with cognitive dysfunction that alters brain connectivity and assessing these altered connectivity patterns has become a topic of increasing interest. In this study, we examine the structural and metabolic connectivity using cortical thickness and [18F] Flouro deoxyglucose (FDG)‐positron emission tomography (PET) to identify the network modification in patient with AD when compared to mild cognitive impairment (MCI). To examine our hypothesis; we quantified a relatively newer graph theory measures including assortativity and modularity. We aimed to unravel the multimodal network alterations using simultaneous MRI‐PET acquisitions.MethodsPatients who underwent simultaneous FDG‐PET and MRI study on a 3T MRI were recruited for this exploratory study. After appropriate pre‐processing of structural‐MRI and PET‐metabolic data, graph measures were obtained using the BRAPH toolbox, and subsequently; global and nodal network measures were used to derive group‐level differences (corrected p<0.05). Regions that revealed significant differences were correlated with the cognitive scores (ACE‐III).Results83 demographically matched patients [MCI (n = 27), and AD (n = 56)] were analysed. There were no significant differences between the groups in the mean age (MCI 63.52 ±9.19 years and AD 63.73 ±9.60 years), gender (M: F) MCI 20:7 and AD 26:30, or the mean duration of disease (MCI 2.23±1.92 and AD 2.95 years) other than ACE scores (MCI‐87.30±5.53 and AD 46.02 ±20.61, p value <0.001) and the CDR (MCI‐very mild and AD‐Moderate and Severe). Patients with AD revealed significantly increased assortativity at the global level in both structural and metabolic connectivity analysis. In addition, metabolic connectivity revealed increased modularity and decreased participation coefficient in patients with AD. Cortical thickness and SUV abnormalities in several regions in bilateral parietotemporal lobes were proportional with the cognitive scores (ACE‐III).ConclusionProbable erroneous and homophilic network segregation paralleling the aging associated loss of whole brain integration was found proportional to the memory scores. Further studies in larger cohorts are required to ascertain the clinical relevance of these findings as an imaging biomarker.

Socioeconomic determinants of cognition among older Brazilian adults: A life‐course approach

AbstractBackgroundThe prevalence of cognitive impairment is higher in low‐ and middle‐income countries compared to high‐income economies. Yet few nationally representative studies from Latin America have investigated life‐course socioeconomic factors related to the susceptibility to age‐associated cognitive impairment. In this study, we examined the associations of early‐ (education and food insecurity), mid‐ (employment stability), and late‐life (any personal income, household per capita income, and self‐perceived income) socioeconomic indicators with the risk of cognitive impairment, while simultaneously exploring whether gender plays an effect‐modifier role on these associations.MethodThe study population comprised Brazilian adults aged 50 years and over (N = 8710) from the Brazilian Longitudinal Study of Aging. Those with ≤ 1.5 SD on a global composite measure of cognition (N = 1005) were assigned to the cognitive impairment group. Unadjusted and mutually adjusted logistic regressions estimated odds ratios with 95% confidence intervals.ResultHigher midlife employment stability and late‐life household per capita income were positively associated with the health of adult cognition. Moreover, secondary analyses performed separately for males and females showed the higher the early‐life educational attainment, the lower the likelihood of impaired cognition among females but not among males. Conversely, having a source of income in old age showed a buffering role against cognitive impairment in males, but this association was not observed in females. No significant associations were noted for early‐life food insecurity or late‐life self‐perceived income.ConclusionThese findings may have implications for population health and health policy by advancing our understanding of socioeconomic determinants of mid‐to‐late‐adulthood cognition.

Elevated Amyloid‐β and Tau Levels in the Brain are Associated with a Reduced Abundance of Neuroprotective Gut Bacteria

AbstractBackgroundRecent research suggests that differences in the gut microbiome composition may contribute to the pathogenesis of neurological disorders, including Alzheimer’s disease (AD). Animal studies have shown that fecal microbiota transplantation reduces amyloid plaques in mouse AD models. However, whether the buildup of Aβ and tau deposits in the brain are associated with shifts in the human gut microbiota composition is understudied.MethodWe used stool specimens and neuropathological measures from 140 middle‐aged individuals (Table 1: mean age 56, 54% Female) from the Framingham Heart Study (FHS) to assess the link between the gut microbiome composition and Aβ Positron Emission Tomography (Aβ‐PET) in a global composite brain measure, and tau‐PET deposits in the rhinal cortex and the inferior temporal cortex. We quantified gut microbiome composition using 16S rRNA sequencing. We performed multivariable association and differential abundance analyses, adjusting for age, sex, body mass index, and other confounders.ResultMultivariable association results (Figure 1) indicated significant associations (adjusted p‐value < 0.001) between both Aβ‐PET and tau‐PET levels with abundance of genera Butyricicoccus and Ruminococcus. Moreover, differential abundance analysis (Figure 2) showed that these bacteria have lower than expected abundance in individuals with elevated Aβ‐PET and tau‐PET measures (Aβ‐PET, Ruminococcus: OR = 0.89, [0.88, 0.91]; Butyricicoccus: OR = 0.77, [0.72, 0.81]); (tau‐PET in the rhinal cortex: Ruminococcus: OR = 0.82, [0.8, 0.83]; Butyricicoccus: OR = 0.91 [0.88, 0.94]); (tau‐PET in the inferotemporal cortex:, Ruminococcus: OR = 0.79 [0.78, 0.81]; Butyricicoccus: OR = 0.83 [0.81, 0.86]). Conversely, we observed an increased abundance of genera Cytophaga (tau‐PET in the rhinal cortex, OR = 1.78, [1.15, 2.75]) and Alistipes (tau‐PET in the rhinal cortex, OR = 1.19, [1.17, 1.22]) in individuals with high Aβ‐PET and tau‐PET levels. Finally, functional analysis showed that Butyricicoccus and Ruminococcus are butyrate‐producing bacteria harboring neuroprotective effects.ConclusionWe showed that elevated measures of Aβ‐PET and tau‐PET in the rhinal and the inferior temporal cortex are associated with a reduced abundance of butyrate‐producing Butyricicoccus and Ruminococcus in the gut of middle‐aged individuals from the FHS. As these bacteria harbor neuroprotective effects, further studies are needed to elucidate underlying mechanisms and assess their therapeutic potential.

An examination of the impact of age and sleep quality on neurocognition within a multi‐ethnic sample

AbstractBackgroundOlder adults and ethnoracially diverse groups (e.g., non‐Latinx Black (NLB), Latinx) are at higher risk of poor sleep quality. Poor sleep is linked to neurocognitive (NC) decline in middle/older adults, but much of the sleep literature has relied on global NC screening measures. This study examined the effects of age and sleep quality on NC functioning within a multi‐ethnic sample of middle/older adults utilizing a multi‐domain NC battery.MethodThis cross‐sectional study included 119 middle/older adults (M age = 65.3, SD age = 6.9; 46% NLB, 31% Latinx, and 23% non‐Latinx White (NLW); 63% female) who completed demographic questionnaires, the Pittsburgh Sleep Quality Index (PSQI), and a comprehensive NC battery. PSQI global and component scores (e.g., Daytime Dysfunction; PSQI‐DD) measured subjective reporting of sleep quality. Demographically‐adjusted NC T‐scores were used to compute 8 NC‐domain and global average T‐scores. Pearson’s correlations, ANOVA, and multiple regressions were used to test hypotheses.ResultGlobal NC was not related to any PSQI components, and the PSQI components did not differ across ethnoracial groups (all p’s<.05). However, within‐group correlations revealed that the relationship between PSQI components and NC domains significantly differed across ethnoracial groups. For example, frequency of sleep medication usage was significantly negatively correlated with executive functioning in the NLB group (r = ‐.39, p = .02), but not NLW or Latinx groups. Multiple regressions, including age and the interactions between race/ethnicity and PSQI component scores, significantly predicted 21‐39% of the variance in all NC domains (p’s<.05), except attention/working memory (p = .60). The interaction between PSQI‐DD and ethnoracial status significantly predicted memory (p’s<.05); this relationship was positive in the NLW group (B = 20.20), yet negative in the NLB (B = ‐1.16) and Latinx (B = ‐0.56) groups (ps<.05).ConclusionDisordered sleep may have a greater impact on NC functioning, namely memory, among middle/older adults from diverse ethnoracial groups, who are already at heightened risk for NC decline. Importantly, global cognitive screening may be insufficient in examining the effects of sleep quality on NC in middle/older adults. Given the ethnoracial differences in sleep quality, future research should consider culturally‐tailored sleep interventions. Using objective sleep quality measures (e.g., actigraphy) may better quantify sleep components.

Association between social networking and cognition among middle aged and older adults in rural India

AbstractBackgroundEmerging evidence suggests that better social networking is associated with better cognitive performance among older adults. However, most of the prior studies have used global cognitive measures to study the above relationship. In this study, we aim to investigate the role of social networking on distinct cognitive domains, among dementia‐free middle‐aged and older‐age adults from a rural Indian population.MethodBaseline assessment data of 2403 participants (≥45 years), who are part of an ongoing, prospective, aging cohort study in rural India (Srinivaspura Aging, NeuroSenescence, and COGnition, SANSCOG) and having a Clinical Dementia Rating (CDR) of ‘0’ who are cognitively healthy was utilized for this study. Social networking was assessed using Cohen’s Social Network Index (SNI), wherein three dimensions were examined – network diversity, number of people in social network and number of embedded networks. Cognitive functions were assessed using episodic memory, geometric figure spatial recognition, verbal fluency, semantic association, word comprehension, reading comprehension and visuospatial span subtests of a culturally validated, computerized, neurocognitive test battery. Linear regression models, adjusted with age and gender were used for statistical analysis.ResultIn the linear regression model, adjusted for age and gender, higher network diversity was significantly associated with better cognitive performance in episodic memory (β = 0.16, p = 0.001), attention function (β = 0.07, p = 0.004), geometric figure spatial recognition (β = 0.13, p = 0.001), verbal fluency phonemic cue (β = 0.11, p = 0.001), reading comprehension (β = 0.09, p = 0.001) and semantic language association function (β = 0.08, p = 0.001). Further, higher dimension of number of people in social network was significantly associated with better cognitive performances in semantic language association function (β = 0.002, p = 0.04). Furthermore, in the third dimension of SNI, higher dimension of number of embedded networks was significantly associated with better cognitive performances in visuospatial span (β = 0.05, p = 0.046) and verbal fluency phonemic cue (β = 0.103, p = 0.001).ConclusionThe findings suggest that better social networking in all three dimensions was associated with better cognitive functions in multiple distinct cognitive domains. It is important to follow‐up these participants longitudinally with serial cognitive monitoring to understand if social networking can potentially delay cognitive decline and thereby, serve as a protective factor for dementia.

History of preoperative COVID‐19 infection and postoperative cognitive change among older adults undergoing major elective surgeries

AbstractBackgroundEmerging evidence suggests that recovery from COVID‐19 infection may be associated with cognitive decline and possibly, incident dementia. Older adults undergoing major surgeries are at heightened risk for postoperative delirium and delayed cognitive recovery; however, it is unknown whether preoperative COVID‐19 infection is associated with worse perioperative cognitive outcomes. Therefore, the objective of this study was to investigate relationships between history of preoperative COVID‐19 infection and cognitive change following major elective surgery.MethodThe study population consisted of cognitively normal adults, ≥ 65years, enrolled in the Cognitive Recovery After Elective Surgery (CREATES) study, an ongoing investigation of BBB function and perioperative cognition. Participants who completed preoperative baseline and 2‐month postoperative assessments were included in the analyses. Cognitive performance (global function (MoCA) and age‐ and education‐adjusted letter fluency, category fluency, learning, memory) at baseline was compared with 2‐month postoperative test results in the entire sample and among those with/without preoperative COVID‐19. Between‐group differences were analyzed using independent samples t‐tests, chi‐square analyses, and repeated measures ANOVAs.ResultA total of 34 participants (mean age, 75 [SD] 4.9 years; 83% White; 54% orthopedic surgery) were included. Of these, 10 reported a preoperative, non‐hospitalized COVID‐19 infection and 24 did not have preoperative COVID‐19. No cases of postoperative delirium were observed. In the full sample, there was evidence of cognitive improvement in letter fluency (F = 5.53, p = 0.03, η2 = 0.18) and memory (F = 4.42, p = 0.04, η2 = 0.12), relative to preoperative baseline. On the MoCA, a global cognitive measure, 86% scored within normal range (MoCA ≥ 26) 2 months after surgery. COVID sub‐groups did not differ on baseline demographics, family history, medical, or cognitive variables (all p’s<0.5). There was no effect of time on change in cognitive test scores (all p’s<0.05) at the 2‐month postoperative assessment.ConclusionIn this modest sample of older surgical patients, history of preoperative COVID‐19 infection was not associated with cognitive decline after surgery; however, postoperative improvement on some cognitive tests was observed in the full sample. Future research in larger populations including biomarkers of neuroinflammation is needed to determine whether older adults with history of COVID‐19 infection are at additional risk of cognitive decline following surgery.

The association of neighborhood socioeconomic status, cognition, cardiovascular risk factors, and vascular risk biomarkers in the HABS‐HD study

AbstractBackgroundNeighborhood socioeconomic status (NSES) is linked to poorer cognition and physical health, influencing the risk of cardiovascular disease and mortality. Adverse neighborhood conditions have been also associated with higher cardiovascular biomarker levels. This study goal is to examine whether NSES is associated with cognitive function and whether this relationship is explained by associations between NSES and cardiovascular risk and biomarker factors in a sample of non‐Hispanic Whites (NHW) and Mexican American (MA) elders.MethodWe studied 1391 subjects from the Health and Aging Brain Study (HABS‐HD) with signed consent, fasting blood samples, 3T MRI, clinical evaluation, and cognitive testing. Area deprivation index (ADI) was used as a measure NSES. Cardiovascular risk factors (CVRF) were ascertained by self‐ report and medical history, and biomarkers were assayed via a multiple‐plex biomarker assay platform using electrochemiluminescence. Three linear regression models examined the association of ADI with cognitive performance, adjusting for age, sex, and education, CVRF, and vascular risk biomarkers.ResultSixty percent of the sample were female. MA were significantly younger, less educated, and had higher ADI scores than NHW. They also had lower scores in global cognition and executive function measures. MA had a higher prevalence of hypertension, diabetes and obesity (p = <0.0001). After controlling for demographic variables, ADI was associated with SEVLT [NHW (B = ‐0.003, t = ‐2.18, p = 0.02); MA (B = ‐0.005, t = ‐2.96, p = 0.003)] and Trails B [NHW (B = ‐0.006, t = ‐2.55, p = 0.01); MA (B = ‐0.01, t = ‐3.76, p = <0.001)] scores in both ethnic groups. Dyslipidemia influenced the association of ADI with SEVLT in MA, while obesity influenced the association of ADI and trails B in NHW. The association of ADI and trails B was partially influenced by IL6 in MA, and this association was partially influenced by TNF, CRP, and VCAM values in NHW.ConclusionNSES may influence cognitive functioning. This relationship is only partially explained by CVRF and vascular blood biomarkers. Future research is needed on the longitudinal relationships of NSES, cognitive impairment, and vascular factors.

Associations of GFAP, NfL, Aβ42/40, and pTau231 with global cognition in LEADS

AbstractBackgroundHistorically, Alzheimer’s disease (AD) biomarkers have been used to identify the presence of pathology and have been shown to change well ahead of symptom onset. While previous research has evaluated plasma pTau231 and its associations with cognition, little to none of this research has focused on early‐onset AD (EOAD) populations. Here we investigate how select plasma biomarkers are associated with global cognitive measures in early‐onset cognitive impairment.MethodThe current sample included 367 Longitudinal Early‐Onset AD Study (LEADS) participants (aged 41 to 65) categorized as amyloid PET‐positive EOAD, amyloid PET‐negative EOnonAD, or cognitively normal (CN). Each participant had baseline global cognitive (Mini‐Mental State Examination [MMSE], Montreal Cognitive Assessment [MoCA], Clinical Dementia Rating Scale sum of boxes [CDR‐SB], and ADAS‐Cog13) and plasma biomarker assessments (Simoa‐HDx N4PE kit: Aβ42/40, phosphorylated Tau [pTau231], Neurofilament light protein [NfL], and glial fibrillary acidic protein [GFAP]). Partial correlations were used to check for associations with cognitive performance controlling for age, sex, and years of education. Fisher r‐to‐z transformations were conducted to compare the performance across diagnostic groups.ResultPartial correlations in the pooled sample showed moderate associations between cognition and plasma pTau231, GFAP and NfL (r = .42‐.50, p<.001) and weaker associations with Aβ42/40 (r = .25‐.33, p<.001). When split into diagnostic groups, the NfL and GFAP correlations were significant in both EOAD and EOnonAD, but not CN. The pTau231 correlations were significant only in EOAD. Aβ42/40 correlations were non‐significant within specific diagnostic groups. No differences were observed in the magnitude of the cognitive and biomarker associations between EOAD and EOnonAD samples (ps>.05).ConclusionAs expected, the neurodegenerative biomarkers pTau231 and NfL showed stronger association with cognition compared to the marker for brain amyloidosis (Aβ42/40). The nonspecific markers for neurodegeneration (NfL) and brain astrogliosis (GFAP) showed associations in both EOAD and EOnonAD while the markers specific to AD were only significant in EOAD. Plasma biomarkers show great promise for AD diagnosis and monitoring.

Versatile MRI acquisition and processing protocol for population‐based neuroimaging

AbstractBackgroundNeuroimaging plays an essential role in epidemiological studies and a special focus is directed towards the employment of versatile MRI acquisition and processing. The proposed multi‐purpose MRI protocol was designed for large‐scale and long‐term population neuroimaging and includes structural, diffusion‐weighted, and functional MRI modalities. It directly links the acquisition of an extensive set of MRI contrasts with fully automated data processing pipelines and quality assurance of the MRI data and image‐derived phenotypes.MethodThe MRI acquisition protocol is largely based on in‐house developed MR sequences. With a total scan time below one hour per participant, it allows to acquire multiple MR contrasts at 3T with whole‐brain coverage and high isotropic image resolution, while keeping potential subject discomfort and motion artifacts at manageable levels. Designed to be kept constant, but also adaptive, the scan protocol separates into a core imaging protocol with MR contrasts of high relevance acquired for all study participants, and a free protocol to accommodate alternative promising MRI techniques in smaller sub‐populations. The analysis protocol handles large‐scale imaging data by means of fast and fully automated processing pipelines that incorporate state‐of‐the‐art image analysis tools and innovative machine learning methods, particularly using deep learning. Dedicated quality assessment (QA) includes visual rating and inspection for incidental findings on structural MRI and QA workflows tailored for each postprocessing pipeline to automatically identify problematic data based on the distribution of subject‐specific QA metrics with respect to the population average.ResultThe MRI protocol has been successfully applied in the Rhineland Study, a prospective cohort study in Bonn, Germany, with currently over 10,000 participants. Image‐derived phenotypes include: global and regional brain tissue volume, thickness and surface measures from multi‐modal structural MRI, global and regional microstructural measures based on diffusion‐weighted MRI, brain functional connectivity using resting‐state functional MRI, and volumes of subcutaneous and visceral adipose tissue based on a single‐breathhold abdominal MRI (Figure 1).ConclusionWe present a versatile MRI protocol with acquisition and analysis methods that are generally applicable and not geared towards a specific disease or research question. Thus, this protocol may be of specific interest for many neuroimaging applications including population imaging studies.

Failed pedestrian street experiments in high-density urban Asia: A matter of policies?

Promoted by sustainable urban agendas and urged by global pandemic measures, street experiments (SE) are booming in Europe but remain latent in Asia. These experiments aim to reconfigure streets as more than spaces for motorized traffic movements, enabling a temporary urban paradigm shift. Such a shift involves balancing active mobility and public space uses in streets while envisioning radically different settings and uses. Recently, eminent scholars urged considering SE in connection to the system and planning framework within which SE are conceived to trace their trajectories. This article examines four decades of temporary-pedestrianization policies and planning instruments in Hong Kong, an Asian city representative of high-density urban environments with highly intensive use of road space and conservative and prescriptive planning. In doing so, the article identifies four trajectories and illustrates two emblematic cases: Chater Road, the first street temporarily pedestrianized under a commercial initiative, and Sai Yeung Choi Street South, a street pedestrianized under a government initiative, now turned back to its original function. The competing roles and practical uses that pedestrianized streets must fulfil partially determined their fate. However, the trajectories these cases followed also differ due to the contextual planning approach and decision-making process. The study contributes to scholarship on SE by shedding new light on the geographical context of high-density urban Asia, forwarding challenges that policymakers might need to address in the planning and governance of SE in similar environments.

Cognitive reserve and resilience of cognitive networks in ageing

AbstractBackgroundIn the ageing process, different cognitive functions decline at different time points and at different rates. Additionally, the inter‐individual variability in cognitive decline could partially depend on cognitive reserve, which represents a resilience factor against age‐related cognitive decline. These complex relationships can be captured with advanced multivariate methods such as graph theory, that can be applied to investigate cognitive networks. The present study aimed to examine the association between cognitive reserve and cognitive networks across age.MethodA total of 334 cognitively healthy participants were stratified into early‐middle‐age (37‐50 years; n = 110), late‐middle‐age (51‐64 years; n = 106), and elderly (65‐78 years; n = 118) groups. Within each age group, individuals were further subdivided into two cognitive reserve levels (high, low) based on a crystallized intelligence proxy. For each subgroup, cognitive networks were constructed based on correlations between 47 z‐scored cognitive variables. Applying graph theory, different global and nodal network measures were compared between subgroups.ResultsGraph‐theoretical analyses revealed that individuals with high cognitive reserve were characterized by a stable cognitive network across age groups. The only consistent difference between the high cognitive reserve groups emerged in modularity with the late‐middle‐age group showing decreased modularity compared to early‐middle‐age and elderly groups. In contrast, individuals with low cognitive reserve showed a marked reconfiguration of cognitive networks across age groups with a pronounced dedifferentiation in late‐middle‐age. This was reflected as a decrease in global efficiency and increase in mean network strength and small‐worldness in the late‐middle‐age group compared to the early‐middle‐age group. The elderly group had a higher global efficiency and lower mean network strength and small‐worldness compared to the late‐middle‐age group.ConclusionA high cognitive reserve was associated with the resilience of the cognitive connectome during the ageing process, while individuals with low cognitive reserve showed prominent changes in their cognitive connectome with increasing age. Gaining further insights into these mechanisms will contribute to our understanding of age‐related cognitive decline and guide the development of strategies to preserve cognitive function in ageing.

Air Pollution Modeling of UNI-DEM Model by using Innovative Stochastic Approaches

In this paper we develop advanced multidimensional sensitivity analysis, based on some innovative stochastic approaches for performing air pollution modelling on a large-scale model of long-range transport of air pollutants. The Unified Danish Eulerian Model (UNI-DEM) is a very important mathematical model, and can be applied in many different studies related to damaging effects caused by high air pollution levels. We shall use it in this paper to get a reliable answer to a some very important questions regrading environmental protection. We develop some advanced Monte Carlo and quasi-Monte Carlo methods, based on special lattice and digital sequences. In this paper we will improve the digital ecosystem modeling by improving the existence stochastic approaches. The computational efficiency (in terms of relative error and computational time) of the advanced Monte Carlo algorithms for multidimensional numerical integration has been studied to analyze the sensitivity of UNI-DEM model output to variation of input emissions of the anthropogenic pollutants and of rates of several chemical reactions. The algorithms will be applied to compute global Sobol sensitivity measures corresponding to the influence of several input parameters on the concentrations of important air pollutants. The study will be done for the areas of several European cities with different geographical locations.

Default mode network sub‐systems connectivity in atypical Alzheimer’s disease

AbstractBackgroundDisruption of default mode network (DMN) connectivity is common in Alzheimer’s disease. We investigated cross‐sectional and one‐year longitudinal changes in DMN sub‐systems in atypical clinical presentations of AD, in relation to age and tau.MethodSixty‐four amyloid‐positive atypical AD (Aty‐AD) patients diagnosed with posterior cortical atrophy (n = 35) or logopenic progressive aphasia (n = 29) were recruited by the Neurodegenerative Research Group. Patients underwent structural and resting‐state functional MRI, and [18F]flortaucipir PET at baseline and one‐year follow‐up. 140 amyloid‐negative cognitively unimpaired (CU) individuals from the Mayo Clinic Study of Aging were included as controls. Global tau SUVR was calculated in a meta‐ROI including parietal, temporal, and occipital regions. DMN connectivity was calculated in native space for posterior (pDMN), ventral (vDMN), anterior ventral (avDMN) and anterior dorsal (adDMN) DMN sub‐systems using the dual regression method. A global measure of DMN connectivity, the Network Failure Quotient (NFQ), was calculated as (vDMN_to_pDMN+ adDMN_to_pDMN)/(pDMN+vDMN). Linear mixed‐effects models were computed for each DMN connectivity measure, including diagnosis (Aty‐AD, CU), age, time and their interaction, and a per‐person random effect. SPM paired t‐tests were run to compare baseline and follow‐up images in Aty‐AD and CU separately. Linear mixed‐effect models were run in the Aty‐AD cohort only to investigate the effect of global baseline tau SUVR on each DMN connectivity measure.ResultMixed‐effects models showed evidence of lower cross‐sectional pDMN and higher adDMN connectivity in Aty‐AD relative to CU, with no significant time effects (Fig. 1). While connectivity in all DMN sub‐systems declined with age in CU, connectivity was higher in older Aty‐AD patients relative to younger, particularly in vDMN and pDMN. A similar trend was observed for NFQ, which was significantly higher in Aty‐AD, with a negative age effect (Fig. 1). In Aty‐AD, voxel‐based analyses showed moderate evidence of decline in vDMN connectivity and increase in avDMN connectivity over time (Fig. 2). Greater baseline global tau SUVR was associated with lower vDMN connectivity, cross‐sectionally and longitudinally (Fig. 3).ConclusionDMN connectivity was altered in Aty‐AD, with strongest alterations in younger patients. The vDMN declined over time, suggesting a shift in DMN connectivity with disease progression that was likely related to tau pathology.