Alzheimer-signature MRI biomarker predicts AD dementia in cognitively normal adults

Pharmacokinetic study and neuropharmacological effects of Atractylenolide Ⅲ to improve cognitive impairment via PI3K/AKT/GSK3β pathway in intracerebroventricular-streptozotocin rats

ETHNOPHARMACOLOGICAL RELEVANCE

The traditional Chinese herbal remedy Atractylodes macrocephala Koidz is renowned for its purported gastrointestinal regulatory properties and immune-enhancing capabilities. Atractylenolide III (ATL III), a prominent bioactive compound in Atractylodes macrocephala Koidz, has demonstrated significant pharmacological activities. However, its impact on neuroinflammation, oxidative stress, and therapeutic potential concerning Alzheimer's disease (AD) remain inadequately investigated.

AIM OF THE STUDY

This study aims to assess the plasma pharmacokinetics of ATL III in Sprague-Dawley (SD) rats and elucidate its neuropharmacological effects on AD via the PI3K/AKT/GSK3β pathway. Through this research, we endeavor to furnish experimental substantiation for the advancement of novel therapeutics centered on ATL III.

MATERIALS AND METHODS

The pharmacokinetic profile of ATL III in SD rat plasma was analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). AD models were induced in SD rats through bilateral intracerebroventricular (ICV) administration of streptozotocin (STZ). ATL III was administered at doses of 0.6 mg/kg, 1.2 mg/kg, and 2.4 mg/kg, while donepezil (1 mg/kg) served as control. Cognitive function assessments were conducted employing behavioral tests including the Morris Water Maze and Novel Object Recognition. Neuronal pathology and histological changes were evaluated through Nissl staining and Hematoxylin-Eosin (HE) staining, respectively. Oxidative stress levels were determined by quantifying malondialdehyde (MDA) content and total superoxide dismutase (T-SOD) activity. Molecular docking analysis was employed to explore the direct binding between ATL III and its relevant targets, followed by validation using Western blot (WB) experiments to assess the expression of p-Tau, PI3K, AKT, GSK3β, and their phosphorylated forms.

RESULTS

Within the concentration range of 5-500 ng/mL, ATL III demonstrated exceptional linearity (R2 = 0.9991), with a quantification limit of 5 ng/mL. In male SD rats, ATL III exhibited a Tmax of 45 minutes, a t1/2 of 172.1 minutes, a Cmax of 1211 ng/L, and an AUC(0-t) of 156031 ng/L*min. Treatment with ATL III significantly attenuated Tau hyperphosphorylation in intracerebroventricular-streptozotocin (ICV-STZ) rats. Furthermore, ATL III administration mitigated neuroinflammation and oxidative stress, as evidenced by reduced Nissl body loss, alleviated histological alterations, decreased MDA content, and enhanced T-SOD activity. Molecular docking analyses revealed strong binding affinity between ATL III and the target genes PI3K, AKT, and GSK3β. Experimental validation corroborated that ATL III stimulated the phosphorylation of PI3K and AKT while reducing the phosphorylation of GSK3β.

CONCLUSIONS

Our results indicate that ATL III can mitigate Tau protein phosphorylation through modulation of the PI3K/AKT/GSK3β pathway. This attenuation consequently ameliorates neuroinflammation and oxidative stress, leading to enhanced learning and memory abilities in ICV-STZ rats.

Relationship between cortical brain atrophy, delirium, and long-term cognitive decline in older surgical patients

In older patients, delirium after surgery is associated with long-term cognitive decline (LTCD). The neural substrates of this association are unclear. Neurodegenerative changes associated with dementia are possible contributors. We investigated the relationship between brain atrophy rates in Alzheimer's disease (AD) and cognitive aging signature regions from magnetic resonance imaging before and one year after surgery, LTCD assessed by the general cognitive performance (GCP) score over 6 years post-operatively, and delirium in 117 elective surgery patients without dementia (mean age = 76). The annual change in cortical thickness was 0.2(1.7) % (AD-signature p = 0.09) and 0.4(1.7) % (aging-signature p = 0.01). Greater atrophy was associated with LTCD (AD-signature: beta(CI) = 0.24(0.06-0.42) points of GCP/mm of cortical thickness; p < 0.01, aging-signature: beta(CI) = 0.55(0.07-1.03); p = 0.03). Atrophy rates were not significantly different between participants with and without delirium. We found an interaction with delirium severity in the association between atrophy and LTCD (AD-signature: beta(CI) = 0.04(0.00-0.08), p = 0.04; aging-signature: beta(CI) = 0.08(0.03-0.12), p < 0.01). The rate of cortical atrophy and severity of delirium are independent, synergistic factors determining postoperative cognitive decline in the elderly.

A comparison of PM2.5 exposure estimates from different estimation methods and their associations with cognitive testing and brain MRI outcomes

BACKGROUND

Reported associations between particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) and cognitive outcomes remain mixed. Differences in exposure estimation method may contribute to this heterogeneity.

OBJECTIVES

To assess agreement between PM2.5 exposure concentrations across 11 exposure estimation methods and to compare resulting associations between PM2.5 and cognitive or MRI outcomes.

METHODS

We used Visit 5 (2011-2013) cognitive testing and brain MRI data from the Atherosclerosis Risk in Communities (ARIC) Study. We derived address-linked average 2000-2007 PM2.5 exposure concentrations in areas immediately surrounding the four ARIC recruitment sites (Forsyth County, NC; Jackson, MS; suburbs of Minneapolis, MN; Washington County, MD) using 11 estimation methods. We assessed agreement between method-specific PM2.5 concentrations using descriptive statistics and plots, overall and by site. We used adjusted linear regression to estimate associations of method-specific PM2.5 exposure estimates with cognitive scores (n = 4678) and MRI outcomes (n = 1518) stratified by study site and combined site-specific estimates using meta-analyses to derive overall estimates. We explored the potential impact of unmeasured confounding by spatially patterned factors.

RESULTS

Exposure estimates from most methods had high agreement across sites, but low agreement within sites. Within-site exposure variation was limited for some methods. Consistently null findings for the PM2.5-cognitive outcome associations regardless of method precluded empirical conclusions about the potential impact of method on study findings in contexts where positive associations are observed. Not accounting for study site led to consistent, adverse associations, regardless of exposure estimation method, suggesting the potential for substantial bias due to residual confounding by spatially patterned factors.

DISCUSSION

PM2.5 estimation methods agreed across sites but not within sites. Choice of estimation method may impact findings when participants are concentrated in small geographic areas. Understanding unmeasured confounding by factors that are spatially patterned may be particularly important in studies of air pollution and cognitive or brain health.

Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence

Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine.

Alzheimer's disease progression detection based on optical fluence rate measurements using alternative laser wavelengths

Alzheimer's disease (AD) levels have increased globally, which is considered the sixth reason for deaths. So, a requirement exists for economic and quantitative methods to follow up the gradual progression of AD. The current study presents a simulation for a non-irradiated, safe, wearable, and noninvasive mobile approach for detecting the progression of Alzheimer's brain atrophy using the optical diffusion technique and for investigating the difference between the normal and the diseased brain. The virtual study was accomplished using COMSOL Multiphysics. The simulated head is implemented as the following: scalp, skull, cerebrospinal fluid, gray matter, and white matter. The optical properties of the heterogeneous tissue are observed using the fluence rate after irradiating the head with different wavelengths (630, 700, 810, 915, and 1000 nm) of lasers. Two assessment techniques were applied to evaluate the brain atrophy measurements; the first technique was an array of photodetectors, which were lined at the head posterior, while a matrix of photodetectors was applied over the head surface in the second technique. The results show that the surface photodetectors approach differentiates the normal from AD brains without measuring the brain atrophy percentages by applying 630 nm. The array of photodetectors distinguishes normal from AD brains without detecting the brain atrophy percentages when the wavelengths 630, 700, and 810 nm were applied. The line detector at 1000 nm evaluates the brain atrophy percentages with AD. The future explores applying those techniques in vivo and analyzing the information by the spectrometer for extensively safer early detection of neural disorders.

Disintegration at the Syntax-Semantics Interface in Prodromal Alzheimer's Disease: New Evidence from Complex Sentence Anaphora in Amnestic Mild Cognitive Impairment (aMCI)

Although diverse language deficits have been widely observed in prodromal Alzheimer's disease (AD), the underlying nature of such deficits and their explanation remains opaque. Consequently, both clinical applications and brain-language models are not well-defined. In this paper we report results from two experiments which test language production in a group of individuals with amnestic Mild Cognitive Impairment (aMCI) in contrast to healthy aging and healthy young. The experiments apply factorial designs informed by linguistic analysis to test two forms of complex sentences involving anaphora (relations between pronouns and their antecedents). Results show that aMCI individuals differentiate forms of anaphora depending on sentence structure, with selective impairment of sentences which involve construal with reference to context (anaphoric coreference). We argue that aMCI individuals maintain core structural knowledge while evidencing deficiency in syntax-semantics integration, thus locating the source of the deficit in the language-thought interface of the Language Faculty.

Clinical predictors of Alzheimer's disease-like brain atrophy in individuals with memory complaints

OBJECTIVES

The definition and assessment methods for subjective cognitive decline (SCD) vary among studies. We aimed to investigate which features or assessment methods of SCD best predict Alzheimer's disease (AD)-related structural atrophy patterns.

METHODS

We assessed 104 individuals aged 55+ with memory complaints but normal cognitive screening. Our research questions were as follows: To improve the prediction of AD related morphological changes, (1) Would the use of a standardized cognitive screening scale be beneficial? (2) Is conducting a thorough neuropsychological evaluation necessary instead of relying solely on cognitive screening tests? (3) Should we apply SCD-plus research criteria, and if so, which criterion would be the most effective? (4) Is it necessary to consider medical and psychiatric comorbidities, vitamin deficiencies, vascular burden on MRI, and family history? We utilized Freesurfer to analyze cortical thickness and regional brain volume meta-scores linked to AD or predicting its development. We employed multiple linear regression models for each variable, with morphology as the dependent variable.

RESULTS

AD-like morphology was associated with subjective complaints in males, individuals with advanced age, and higher education. Later age of onset for complaints, complaints specifically related to memory, excessive deep white matter vascular lesions, and using medications that have negative implications for cognitive health (according to the Beers criteria) were predictive of AD-related morphology. The subjective cognitive memory questionnaire scores were found to be a better predictor of reduced volumes than a single-question assessment. It is important to note that not all SCD-plus criteria were evaluated in this study, particularly the APOE genotype, amyloid, and tau status, due to resource limitations.

CONCLUSIONS

The detection of AD-related structural changes is impacted by demographics and assessment methods. Standardizing SCD assessment methods can enhance predictive accuracy.

Brain Healthcare Quotient as a Tool for Standardized Approach in Brain Healthcare Interventions

In addressing the challenge of assessing healthy brain aging across diverse interventions, this study introduces the use of MRI-derived Brain Healthcare Quotients (BHQ) for comprehensive evaluation. We analyzed BHQ changes in 319 participants aged 24-69, who were allocated into dietary (collagen peptide, euglena, matcha, isohumulone, xanthophyll) and physical activity (hand massage with lavender oil, handwriting, office stretching, pink lens, clinical art) groups, alongside a control group, over a month. These interventions were specifically chosen to test the efficacy of varying health strategies on brain health, measured through BHQ indices: GM-BHQ for gray matter volume, and FA-BHQ for white matter integrity. Notably, significant improvements in FA-BHQ were observed in the collagen peptide group, with marginal increases in the hand massage and office stretching groups. These findings highlight BHQ's potential as a sensitive tool for detecting brain health changes, offering evidence that low-intensity, easily implemented interventions can have beneficial effects on brain health. Moreover, BHQ allows for the systematic evaluation of such interventions using standard statistical approaches, suggesting its value in future brain healthcare research.

Sensitivity of unconstrained quantitative magnetization transfer MRI to Amyloid burden in preclinical Alzheimer's disease

Introduction

Magnetization transfer MRI is sensitive to semi-solid macromolecules, including amyloid beta, and has been used to discriminate Alzheimer's disease (AD) patients from controls. Here, we utilize an unconstrained 2-pool quantitative MT (qMT) approach that quantifies the longitudinal relaxation rates of free water and semi-solids separately, and investigate its sensitivity to amyloid accumulation in preclinical subjects.

Methods

We recruited 15 cognitively normal subjects, of which nine were amyloid positive by [ 18 F]Florbetaben PET. A 12 min qMT scan was used to estimate the unconstrained 2-pool qMT parameters. Group comparisons and correlations were analyzed at the lobar level.

Results

The exchange rate and semi-solid pool's were sensitive to the amyloid concentration. The former finding is consistent with previous reports in clinical AD, but the latter is novel as its value is typically constrained.

Discussion

qMT MRI may be a promising surrogate marker of amyloid beta without the need for contrast agents or radiotracers.

Medial Temporal Lobe Atrophy in Older Adults With Subjective Cognitive Impairments Affects Gait Parameters in the Spatial Navigation Task

Both navigation abilities and gait can be affected by the atrophy in the medial temporal cortex. This study aimed to determine whether navigation abilities could differentiate seniors with and without medial temporal lobe atrophy who complained about their cognitive status. The participants, classified to either the medial temporal atrophy group (n = 23) or the control group (n = 22) underwent neuropsychological assessment and performed a spatial navigation task while their gait parameters were recorded. The study showed no significant differences between the two groups in memory, fluency, and semantic knowledge or typical measures of navigating abilities. However, gait parameters, particularly the propulsion index during certain phases of the navigation task, distinguished between seniors with and without medial temporal lobe lesions. These findings suggest that the gait parameters in the navigation task may be a valuable tool for identifying seniors with cognitive complaints and subtle medial temporal atrophy.

Genetic risk score for Alzheimer's disease predicts brain volume differences in mid and late life in UK biobank participants

INTRODUCTION

We estimated the ages when associations between Alzheimer's disease (AD) genes and brain volumes begin among middle-aged and older adults.

METHODS

Among 45,616 dementia-free participants aged 45-80, linear regressions tested whether genetic risk score for AD (AD-GRS) had age-dependent associations with 38 regional brain magnetic resonance imaging volumes. Models were adjusted for sex, assessment center, genetic ancestry, and intracranial volume.

RESULTS

AD-GRS modified the estimated effect of age (per decade) on the amygdala (-0.41 mm3 [-0.42, -0.40]); hippocampus (-0.45 mm3 [-0.45, -0.44]), nucleus accumbens (-0.55 mm3 [-0.56, -0.54]), thalamus (-0.38 mm3 [-0.39, -0.37]), and medial orbitofrontal cortex (-0.23 mm3 [-0.24, -0.22]). Trends began by age 45 for the nucleus accumbens and thalamus, 48 for the hippocampus, 51 for the amygdala, and 53 for the medial orbitofrontal cortex. An AD-GRS excluding apolipoprotein E (APOE) was additionally associated with entorhinal and middle temporal cortices.

DISCUSSION

APOE and other genes that increase AD risk predict lower hippocampal and other brain volumes by middle age.

Association between structural brain MRI abnormalities and epilepsy in older adults

OBJECTIVE

To determine the association between brain MRI abnormalities and incident epilepsy in older adults.

METHODS

Men and women (ages 45-64 years) from the Atherosclerosis Risk in Communities study were followed up from 1987 to 2018 with brain MRI performed between 2011 and 2013. We identified cases of incident late-onset epilepsy (LOE) with onset of seizures occurring after the acquisition of brain MRI. We evaluated the relative pattern of cortical thickness, subcortical volume, and white matter integrity among participants with incident LOE after MRI in comparison with participants without seizures. We examined the association between MRI abnormalities and incident LOE using Cox proportional hazards regression. Models were adjusted for demographics, hypertension, diabetes, smoking, stroke, and dementia status.

RESULTS

Among 1251 participants with brain MRI data, 27 (2.2%) developed LOE after MRI over a median of 6.4 years (25-75 percentile 5.8-6.9) of follow-up. Participants with incident LOE after MRI had higher levels of cortical thinning and white matter microstructural abnormalities before seizure onset compared to those without seizures. In longitudinal analyses, greater number of abnormalities was associated with incident LOE after controlling for demographic factors, risk factors for cardiovascular disease, stroke, and dementia (gray matter: hazard ratio [HR]: 2.3, 95% confidence interval [CI]: 1.0-4.9; white matter diffusivity: HR: 3.0, 95% CI: 1.2-7.3).

INTERPRETATION

This study demonstrates considerable gray and white matter pathology among individuals with LOE, which is present prior to the onset of seizures and provides important insights into the role of neurodegeneration, both of gray and white matter, and the risk of LOE.

Plasma neurofilament light chain in relation to 10-year change in cognition and neuroimaging markers: a population-based study

Neurofilament light chain (NfL) is a promising biomarker for risk stratification and disease monitoring of dementia, but its utility in the preclinical disease stage remains uncertain. We determined the association of plasma NfL with (change in) neuroimaging markers and cognition in the population-based Rotterdam Study, using linear and logistic regression and mixed-effects models. Plasma NfL levels were measured using the Simoa NF-light™ assay in 4705 dementia-free participants (mean age 71.9 years, 57% women), who underwent cognitive assessment and brain MRI with repeated assessments over a 10-year follow-up period. Higher plasma NfL was associated with worse cognitive performance at baseline (g-factor: β =  - 0.12 (- 0.15; - 0.09), p < 0.001), and accelerated cognitive decline during follow-up on the Stroop color naming task (β = 0.04 (0.02; 0.06), p < 0.001), with a smaller trend for decline in global cognition (g-factor β =  - 0.02 (- 0.04; 0.00), p = 0.044). In the subset of 975 participants with brain MRI, higher NfL was associated with poorer baseline white matter integrity (e.g., global mean diffusivity: β = 0.12 (0.06; 0.19), p < 0.001), with similar trends for volume of white matter hyperintensities (β = 0.09 (0.02; 0.16), p = 0.011) and presence of lacunes (OR = 1.55 (1.13; 2.14), p = 0.007). Plasma NfL was not associated with volumes or thickness of the total gray matter, hippocampus, or Alzheimer signature regions. In conclusion, higher plasma NfL levels are associated with cognitive decline and larger burden of primarily white matter pathology in the general population.

Resting-state functional connectivity and cognitive performance in aging adults with cognitive decline: A data-driven multivariate pattern analysis

BACKGROUND

Cognitive impairments occur on a continuous spectrum in multiple cognitive domains showing individual variability of the deteriorating patterns; however, often, cognitive domains are studied separately.

METHODS

The present study investigated aging individual variations of cognitive abilities and related resting-state functional connectivity (rsFC) using data-driven approach. Cognitive and neuroimaging data were obtained from 62 elderly outpatients with cognitive decline. Principal component analysis (PCA) was conducted on the cognitive data to determine patterns of cognitive performance, then data-driven whole-brain connectome multivariate pattern analysis (MVPA) was applied on the neuroimaging data to discover neural regions associated with the cognitive characteristic.

RESULTS

The first component (PC1) delineated an overall decline in all domains of cognition, and the second component (PC2) represented a compensatory relationship within basic cognitive functions. MVPA indicated rsFC of the cerebellum lobule VIII and insula with the default-mode network, frontoparietal network, and salience network inversely correlated with PC1 scores. Additionally, PC2 score was related to rsFC patterns with temporal pole and occipital cortex.

CONCLUSIONS

The featured primary cognitive characteristic depicted the importance of the cerebellum and insula connectivity patterns in of the general cognitive decline. The findings also discovered a secondary characteristic that communicated impaired interactions within the basic cognitive function, which was independent from the impairment severity.

Cardiovascular risk burden, dementia risk and brain structural imaging markers: a study from UK Biobank

Background

Cardiovascular risk burden is associated with dementia risk and neurodegeneration-related brain structure, while the role of genetics and incident cardiovascular disease (CVD) remains unclear.

Aims

To examine the association of overall cardiovascular risk burden with the risk of major dementia subtypes and volumes of related brain regions in a large sample, and to explore the role of genetics and CVD onset.

Methods

A prospective study among 354 654 participants free of CVD and dementia (2006-2010, mean age 56.4 years) was conducted within the UK Biobank, with brain magnetic resonance imaging (MRI) measurement available for 15 104 participants since 2014. CVD risk burden was evaluated by the Framingham General Cardiovascular Risk Score (FGCRS). Dementia diagnosis was ascertained from inpatient and death register data.

Results

Over a median 12.0-year follow-up, 3998 all-cause dementia cases were identified. Higher FGCRS was associated with increased all-cause dementia risk after adjusting for demographic, major lifestyle, clinical factors and the polygenic risk score (PRS) of Alzheimer's disease. Comparing the high versus low tertile of FGCRS, the odds ratios (ORs) and 95% confidence intervals (CIs) were 1.26 (1.12 to 1.41) for all-cause dementia, 1.67 (1.33 to 2.09) for Alzheimer's disease and 1.53 (1.07 to 2.16) for vascular dementia (all ptrend<0.05). Incident stroke and coronary heart disease accounted for 14% (95% CI: 9% to 21%) of the association between FGCRS and all-cause dementia. Interactions were not detected for FGCRS and PRS on the risk of any dementia subtype. We observed an 83% (95% CI: 47% to 128%) higher all-cause dementia risk comparing the high-high versus low-low FGCRS-PRS category. For brain volumes, higher FGCRS was associated with greater log-transformed white matter hyperintensities, smaller cortical volume and smaller grey matter volume.

Conclusions

Our findings suggest that the positive association of cardiovascular risk burden with dementia risk also applies to major dementia subtypes. The association of cardiovascular risk burden with all-cause dementia is largely independent of CVD onset and genetic predisposition to dementia.

Pulse pressure and APOE ε4 dose interact to affect cerebral blood flow in older adults without dementia

This study assessed whether the effect of vascular risk on cerebral blood flow (CBF) varies by gene dose of apolipoprotein (APOE) ε4 alleles. 144 older adults without dementia from the Alzheimer's Disease Neuroimaging Initiative underwent arterial spin labeling and T1-weighted MRI, APOE genotyping, fluorodeoxyglucose positron emission tomography (FDG-PET), lumbar puncture, and blood pressure (BP) assessment. Vascular risk was assessed using pulse pressure (systolic BP - diastolic BP). CBF was examined in six AD-vulnerable regions: entorhinal cortex, hippocampus, inferior temporal cortex, inferior parietal cortex, rostral middle frontal gyrus, and medial orbitofrontal cortex. Linear regressions tested the interaction between APOE ε4 dose and pulse pressure on CBF in each region, adjusting for age, sex, cognitive classification, antihypertensive medication use, FDG-PET, reference CBF region, and AD biomarker positivity. There was a significant interaction between pulse pressure and APOE ɛ4 dose on CBF in the entorhinal cortex, hippocampus, and inferior parietal cortex, such that higher pulse pressure was associated with lower CBF only among ε4 homozygous participants. These findings demonstrate that the association between pulse pressure and regional CBF differs by APOE ε4 dose, suggesting that targeting modifiable vascular risk factors may be particularly important for those genetically at risk for AD.

More Similar than Different: Memory, Executive Functions, Cortical Thickness, and Glucose Metabolism in Biomarker-Positive Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia

Background

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are typically associated with very different clinical and neuroanatomical presentations; however, there is increasing recognition of similarities.

Objective

To examine memory and executive functions, as well as cortical thickness, and glucose metabolism in AD and bvFTD signature brain regions.

Methods

We compared differences in a group of biomarker-defined participants with Alzheimer's disease and a group of clinically diagnosed participants with bvFTD. These groups were also contrasted with healthy controls (HC).

Results

As expected, memory functions were generally more impaired in AD, followed by bvFTD, and both clinical groups performed more poorly than the HC group. Executive function measures were similar in AD compared to bvFTD for motor sequencing and go/no-go, but bvFTD had more difficulty with a set shifting task. Participants with AD showed thinner cortex and lower glucose metabolism in the angular gyrus compared to bvFTD. Participants with bvFTD had thinner cortex in the insula and temporal pole relative to AD and healthy controls, but otherwise the two clinical groups were similar for other frontal and temporal signature regions.

Conclusions

Overall, the results of this study highlight more similarities than differences between AD and bvFTD in terms of cognitive functions, cortical thickness, and glucose metabolism. Further research is needed to better understand the mechanisms mediating this overlap and how these relationships evolve longitudinally.

Examining the relationship between anxiety and regional brain volumes in the National Alzheimer's Coordinating Center uniform, imaging, and biomarker datasets

Anxiety has been associated with a greater risk of Alzheimer's disease (AD). Existing research has identified structural differences in regional brain tissue in participants with anxiety, but results have been inconsistent. We sought to determine the association between anxiety and regional brain volumes, and the moderation effect of APOE ε4. Using data from participants in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set, with complete imaging (MRI) and biomarker data (n = 1533), multiple linear regression estimated the adjusted effect of anxiety on 30 structural MRI regions. The moderation effect of APOE ε4 on the relation between structural MRI regions and anxiety was assessed as was the moderation effect of cognitive status. False discovery rate was used to adjust for multiple comparisons. After controlling for intracranial volume, age, sex, years of education, race, Hispanic ethnicity, and cognitive status, seven MRI regions demonstrated lower volumes among participants with anxiety: total cerebrum gray matter volume, right hippocampus volume, hippocampal volume (total), right and left frontal lobe cortical gray matter volume, and right and total temporal lobe cortical gray matter volume. Findings suggest that anxiety is associated with significant atrophy in multiple brain regions, with corresponding ventricular enlargement. Future research should investigate if anxiety-related changes to brain morphology contribute to greater AD risk.

Rates of cortical thinning in Alzheimer's disease signature regions associate with vascular burden but not with β-amyloid status in cognitively normal adults at age 70

BACKGROUND

Consistent patterns of reduced cortical thickness have been identified in early Alzheimer's disease (AD). However, the pathological factors that influence rates of cortical thinning within these AD signature regions remain unclear.

METHODS

Participants were from the Insight 46 substudy of the MRC National Survey of Health and Development (NSHD; 1946 British birth cohort), a prospective longitudinal cohort study. Linear regression was used to examine associations of baseline cerebral β-amyloid (Aβ) deposition, measured using florbetapir positron emission tomography, and baseline white matter hyperintensity volume (WMHV) on MRI, a marker of cerebral small vessel disease, with subsequent longitudinal changes in AD signature cortical thickness quantified from baseline and repeat MRI (mean [SD] interval 2.4 [0.2] years).

RESULTS

In a population-based sample of 337 cognitively normal older white adults (mean [SD] age at baseline 70.5 [0.6] years; 48.1% female), higher global WMHV at baseline related to faster subsequent rates of cortical thinning in both AD signature regions (~0.15%/year faster per 10 mL additional WMHV), whereas baseline Aβ status did not. Among Aβ positive participants (n=56), there was some evidence that greater global Aβ standardised uptake value ratio at baseline related to faster cortical thinning in the AD signature Mayo region, but this did not reach statistical significance (p=0.08).

CONCLUSIONS

Cortical thinning within AD signature regions may develop via cerebrovascular pathways. Perhaps reflecting the age of the cohort and relatively low prevalence of Aβ-positivity, robust Aβ-related differences were not detected. Longitudinal follow-up incorporating additional biomarkers will allow assessment of how these relationships evolve closer to expected dementia onset.

Machine Learning-Derived MRI-Based Neurodegeneration Biomarker for Alzheimer's Disease: A Multi-Database Validation Study

BACKGROUND

Pilot study showed that Alzheimer's disease resemblance atrophy index (AD-RAI), a machine learning-derived MRI-based neurodegeneration biomarker of AD, achieved excellent diagnostic performance in diagnosing AD with moderate to severe dementia.

OBJECTIVE

The primary objective was to validate and compare the performance of AD-RAI with conventional volumetric hippocampal measures in diagnosing AD with mild dementia. The secondary objectives were 1) to investigate the association between imaging biomarkers with age and gender among cognitively unimpaired (CU) participants; 2) to analyze whether the performance of differentiating AD with mild dementia from CU will improve after adjustment for age/gender.

METHODS

AD with mild dementia (n = 218) and CU (n = 1,060) participants from 4 databases were included. We investigated the area under curve (AUC), sensitivity, specificity, and balanced accuracy of AD-RAI, hippocampal volume (HV), and hippocampal fraction (HF) in differentiating between AD and CU participants. Among amyloid-negative CU participants, we further analyzed correlation between the biomarkers with age/gender. We also investigated whether adjustment for age/gender will affect performance.

RESULTS

The AUC of AD-RAI (0.93) was significantly higher than that of HV (0.89) and HF (0.89). Subgroup analysis among A + AD and A- CU showed that AUC of AD-RAI (0.97) was also higher than HV (0.94) and HF (0.93). Diagnostic performance of AD-RAI and HF was not affected by age/gender while that of HV improved after age adjustment.

CONCLUSIONS

AD-RAI achieves excellent clinical validity and outperforms conventional volumetric hippocampal measures in aiding the diagnosis of AD mild dementia without the need for age adjustment.

Long-Term PM2.5 Exposure, Lung Function, and Cognitive Function Among Middle-Aged and Older Adults in China

BACKGROUND

Long-term exposure to PM2.5 is related to poor lung function and cognitive impairment, but less is known about the pathway involved in this association. We aimed to explore whether the effect of PM2.5 on cognitive function was mediated by lung function.

METHODS

A total of 7 915 adults older than 45 years old were derived from the China Health and Retirement Longitudinal Study (CHARLS) collected in 2011 and 2015. PM2.5 exposure was estimated using a geographically weighted regression model. Lung function was measured by peak expiratory flow (PEF). Cognitive function was evaluated through a structured questionnaire with 4 dimensions: episodic memory, attention, orientation, and visuoconstruction. Under the counterfactual framework, causal mediation analysis was applied to examine direct and indirect associations.

RESULTS

An interquartile range (IQR) increase in PM2.5 change was significantly related to an 8.480 (95% confidence interval [CI]: 3.116, 13.845) decrease in PEF change and a 0.301 (95% CI: 0.100, 0.575) decrease in global cognitive score change. The direct and indirect effects of PM2.5 exposure on global cognitive performance were -0.279 (95% CI: -0.551, -0.060) and -0.023 (95% CI: -0.041, -0.010), respectively. The proportion of the indirect effect was 7.48% (p = .010). The same significant association appeared in only 2 dimensions, episodic memory and attention, which were both mediated by PEF.

CONCLUSIONS

Lung function played a partially mediating role in the association between long-term PM2.5 exposure and cognition. More clean air actions should be undertaken to improve lung function and cognitive function in older adults.

The Sporadic Early-onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) Cohort

INTRODUCTION

Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker.

METHODS

We analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment.

RESULTS

The EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment.

DISCUSSION

The EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD.

HIGHLIGHTS

We developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.

A review of novel Cognitive Challenge Tests for the assessment of preclinical Alzheimer's disease

OBJECTIVES

There is currently a lack of consensus among neuropsychologists about which cognitive assessment paradigms hold the most promise in identifying subtle cognitive deficits in preclinical Alzheimer's Disease (AD) and which are most useful for monitoring risk of cognitive deterioration. Many widely used instruments are older versions of tests originally developed for the assessment of dementia or traumatic brain injury. Current efforts to digitize these measures provides more uniform and remote assessment, which is an advancement, but does not reflect significant changes in paradigmatic underpinnings or recent advances in cognitive neuroscience.

METHOD

This work provides an overview of novel Cognitive Challenge Tests (CCTs) that employ semantic interference paradigms that uniquely measure the failure to recover from proactive semantic interference (frPSI). Other salient methods to measure meaningful cognitive change in early stage AD are also presented, as well as how they compare with traditional neuropsychological assessments. Finally, future directions for the development of more effective assessment paradigms are discussed.

RESULTS

frPSI is a cognitive marker which measures the persistent inability to learn new semantically competing stimuli despite multiple opportunities to do so. frPSI and deficits in semantic inhibitory control have repeatedly shown utility for the early detection of AD during its preclinical stages. These novel cognitive markers have been related to various biomarkers of AD and neurodegeneration among culturally diverse older adults.

CONCLUSIONS

To meet the critical needs of a rapidly evolving field, cognitive assessment instruments must show sufficient scientific rigor including robust sensitivity, specificity, and predictive utility among culturally and linguistically diverse populations and importantly, be correlated to AD biomarkers. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Higher cortical thickness/volume in Alzheimer's-related regions: protective factor or risk factor?

Some evidence suggests a biphasic pattern of changes in cortical thickness wherein higher, rather than lower, thickness is associated with very early Alzheimer's disease (AD) pathology. We examined whether integrating information from AD brain signatures based on mean diffusivity (MD) can aid in the interpretation of cortical thickness/volume as a risk factor for future AD-related changes. Participants were 572 men in the Vietnam Era Twin Study of Aging who were cognitively unimpaired at baseline (mean age = 56 years; range = 51-60). Individuals with both high thickness/volume signatures and high MD signatures at baseline had lower cortical thickness/volume in AD signature regions and lower episodic memory performance 12 years later compared to those with high thickness/volume and low MD signatures at baseline. Groups did not differ in level of young adult cognitive reserve. Our findings are in line with a biphasic model in which increased cortical thickness may precede future decline and establish the value of examining cortical MD alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes.

Genetic and Environmental Influences on Structural and Diffusion-Based Alzheimer's Disease Neuroimaging Signatures Across Midlife and Early Old Age

BACKGROUND

Composite scores of magnetic resonance imaging-derived metrics in brain regions associated with Alzheimer's disease (AD), commonly termed AD signatures, have been developed to distinguish early AD-related atrophy from normal age-associated changes. Diffusion-based gray matter signatures may be more sensitive to early AD-related changes compared with thickness/volume-based signatures, demonstrating their potential clinical utility. The timing of early (i.e., midlife) changes in AD signatures from different modalities and whether diffusion- and thickness/volume-based signatures each capture unique AD-related phenotypic or genetic information remains unknown.

METHODS

Our validated thickness/volume signature, our novel mean diffusivity (MD) signature, and a magnetic resonance imaging-derived measure of brain age were used in biometrical analyses to examine genetic and environmental influences on the measures as well as phenotypic and genetic relationships between measures over 12 years. Participants were 736 men from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) (baseline/wave 1: mean age [years] = 56.1, SD = 2.6, range = 51.1-60.2). Subsequent waves occurred at approximately 5.7-year intervals.

RESULTS

MD and thickness/volume signatures were highly heritable (56%-72%). Baseline MD signatures predicted thickness/volume signatures over a decade later, but baseline thickness/volume signatures showed a significantly weaker relationship with future MD signatures. AD signatures and brain age were correlated, but each measure captured unique phenotypic and genetic variance.

CONCLUSIONS

Cortical MD and thickness/volume AD signatures are heritable, and each signature captures unique variance that is also not explained by brain age. Moreover, results are in line with changes in MD emerging before changes in cortical thickness, underscoring the utility of MD as a very early predictor of AD risk.

Brain morphometry in older adults with and without dementia using extremely rapid structural scans

T1-weighted structural MRI is widely used to measure brain morphometry (e.g., cortical thickness and subcortical volumes). Accelerated scans as fast as one minute or less are now available but it is unclear if they are adequate for quantitative morphometry. Here we compared the measurement properties of a widely adopted 1.0 mm resolution scan from the Alzheimer's Disease Neuroimaging Initiative (ADNI = 5'12'') with two variants of highly accelerated 1.0 mm scans (compressed-sensing, CSx6 = 1'12''; and wave-controlled aliasing in parallel imaging, WAVEx9 = 1'09'') in a test-retest study of 37 older adults aged 54 to 86 (including 19 individuals diagnosed with a neurodegenerative dementia). Rapid scans produced highly reliable morphometric measures that largely matched the quality of morphometrics derived from the ADNI scan. Regions of lower reliability and relative divergence between ADNI and rapid scan alternatives tended to occur in midline regions and regions with susceptibility-induced artifacts. Critically, the rapid scans yielded morphometric measures similar to the ADNI scan in regions of high atrophy. The results converge to suggest that, for many current uses, extremely rapid scans can replace longer scans. As a final test, we explored the possibility of a 0'49'' 1.2 mm CSx6 structural scan, which also showed promise. Rapid structural scans may benefit MRI studies by shortening the scan session and reducing cost, minimizing opportunity for movement, creating room for additional scan sequences, and allowing for the repetition of structural scans to increase precision of the estimates.

Baseline long-term potentiation-like cortical plasticity is associated with longitudinal cortical thinning in healthy adults and in adults with bipolar disorder type II

The precise neurobiological processes underlying cerebral cortical thinning in aging and psychiatric illnesses remain undetermined, yet aging- and synaptic dysfunction-related loss of synapses are potentially important mechanisms. We used long-term potentiation-like plasticity of the visual evoked potential as an index of synaptic function in the cortex and hypothesized that plasticity at baseline would be negatively associated with future cortical thinning in healthy adults and in adults with bipolar disorder type II. Thirty-two healthy adults and 15 adults with bipolar disorder type II underwent electroencephalography-based measurement of visual evoked potential plasticity and 3T magnetic resonance imaging of the brain at baseline and a follow-up brain scan on average 2.3 years later. The relationships between visual evoked potential plasticity at baseline and longitudinal cortical thickness changes were examined using Freesurfer and the Permutation Analysis of Linear Models tool. The analyses showed a negative association between the plasticity of the N1 visual evoked potential amplitude at baseline and thinning rate in the medial and lateral parietal and medial occipital cortices in healthy adults and in the right medial occipital cortex in the total sample of healthy adults and adults with bipolar disorder type II, indicating greater thinning over time in subjects with less N1 plasticity (pFWER  < .05). Although preliminary, the results indicate an association between visual evoked potential plasticity and the future rate of cortical thinning in healthy adults and in bipolar disorder type II, supporting the hypothesis that cortical thinning might be related to synaptic dysfunction.

Altered gut microbiota in older adults with mild cognitive impairment: a case-control study

Introduction

The microbiota-gut-brain axis is implicated in Alzheimer's disease. Gut microbiota alterations in mild cognitive impairment (MCI) are inconsistent and remain to be understood. This study aims to investigate the gut microbial composition associated with MCI, cognitive functions, and structural brain differences.

Methods

A nested case-control study was conducted in a community-based prospective cohort where detailed cognitive functions and structural brain images were collected. Thirty-one individuals with MCI were matched to sixty-five cognitively normal controls by age strata, gender, and urban/rural area. Fecal samples were examined using 16S ribosomal RNA (rRNA) V3-V4 sequencing. Compositional differences between the two groups were identified and correlated with the cognitive functions and volumes/thickness of brain structures.

Results

There was no significant difference in alpha and beta diversity between MCIs and cognitively normal older adults. However, the abundance of the genus Ruminococcus, Butyricimonas, and Oxalobacter decreased in MCI patients, while an increased abundance of nine other genera, such as Flavonifractor, were found in MCIs. Altered genera discriminated MCI patients well from controls (AUC = 84.0%) and were associated with attention and executive function.

Conclusion

This study provides insights into the role of gut microbiota in the neurodegenerative process.

Brain structure and allelic associations in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD), the most prevalent form of dementia, affects 6.5 million Americans and over 50 million people globally. Clinical, genetic, and phenotypic studies of dementia provide some insights of the observed progressive neurodegenerative processes, however, the mechanisms underlying AD onset remain enigmatic.

AIMS

This paper examines late-onset dementia-related cognitive impairment utilizing neuroimaging-genetics biomarker associations.

MATERIALS AND METHODS

The participants, ages 65-85, included 266 healthy controls (HC), 572 volunteers with mild cognitive impairment (MCI), and 188 Alzheimer's disease (AD) patients. Genotype dosage data for AD-associated single nucleotide polymorphisms (SNPs) were extracted from the imputed ADNI genetics archive using sample-major additive coding. Such 29 SNPs were selected, representing a subset of independent SNPs reported to be highly associated with AD in a recent AD meta-GWAS study by Jansen and colleagues.

RESULTS

We identified the significant correlations between the 29 genomic markers (GMs) and the 200 neuroimaging markers (NIMs). The odds ratios and relative risks for AD and MCI (relative to HC) were predicted using multinomial linear models.

DISCUSSION

In the HC and MCI cohorts, mainly cortical thickness measures were associated with GMs, whereas the AD cohort exhibited different GM-NIM relations. Network patterns within the HC and AD groups were distinct in cortical thickness, volume, and proportion of White to Gray Matter (pct), but not in the MCI cohort. Multinomial linear models of clinical diagnosis showed precisely the specific NIMs and GMs that were most impactful in discriminating between AD and HC, and between MCI and HC.

CONCLUSION

This study suggests that advanced analytics provide mechanisms for exploring the interrelations between morphometric indicators and GMs. The findings may facilitate further clinical investigations of phenotypic associations that support deep systematic understanding of AD pathogenesis.

Morphological and Structural Network Analysis of Sporadic Alzheimer's Disease Brains Based on the APOE4 Gene

BACKGROUND

Alzheimer's disease (AD) is an increasingly common type of dementia. Apolipoprotein E (APOE) gene is a strong risk factor for AD.

OBJECTIVE

Here, we explored alterations in grey matter structure (GMV) and networks in AD, as well as the effects of the APOEɛ4 allele on neuroimaging regions based on structural magnetic resonance imaging (sMRI).

METHODS

All subjects underwent an sMRI scan. GMV and cortical thickness were calculated using voxel-based morphological analysis, and structural networks were constructed based on graph theory analysis to compare differences between AD and normal controls.

RESULTS

The volumes of grey matter in the bilateral inferior temporal gyrus, right middle temporal gyrus, right inferior parietal lobule, right limbic lobe, right frontal lobe, left anterior cingulate gyrus, and bilateral olfactory cortex of patients with AD were significantly decreased. The cortical thickness in patients with AD was significantly reduced in the left lateral occipital lobe, inferior parietal lobe, orbitofrontal region, precuneus, superior parietal gyrus, right precentral gyrus, middle temporal gyrus, pars opercularis gyrus, insular gyrus, superior marginal gyrus, bilateral fusiform gyrus, and superior frontal gyrus. In terms of local properties, there were significant differences between the AD and control groups in these areas, including the right bank, right temporalis pole, bilateral middle temporal gyrus, right transverse temporal gyrus, left postcentral gyrus, and left parahippocampal gyrus.

CONCLUSION

There were significant differences in the morphological and structural covariate networks between AD patients and healthy controls under APOEɛ4 allele effects.

Cortical thinning in chemotherapy-treated older long-term breast cancer survivors

Cognitive decline is an increasing issue for cancer survivors, especially for older adults, as chemotherapy affects brain structure and function. The purpose of this single center study was to evaluate alterations in cortical thickness and cognition in older long-term survivors of breast cancer who had been treated with chemotherapy years ago. In this prospective cohort study, we enrolled 3 groups of women aged ≥ 65 years with a history of stage I-III breast cancer who had received adjuvant chemotherapy 5 to 15 years ago (chemotherapy group, C +), age-matched women with breast cancer but no chemotherapy (no-chemotherapy group, C-) and healthy controls (HC). All participants underwent brain magnetic resonance imaging and neuropsychological testing with the NIH Toolbox Cognition Battery at time point 1 (TP1) and again at 2 years after enrollment (time point 2 (TP2)). At TP1, there were no significant differences in cortical thickness among the 3 groups. Longitudinally, the C + group showed cortical thinning in the fusiform gyrus (p = 0.006, effect size (d) = -0.60 [ -1.86, -0.66]), pars triangularis (p = 0.026, effect size (d) = -0.43 [-1.68, -0.82]), and inferior temporal lobe (p = 0.026, effect size (d) = -0.38 [-1.62, -0.31]) of the left hemisphere. The C + group also showed decreases in neuropsychological scores such as the total composite score (p = 0.01, effect size (d) = -3.9726 [-0.9656, -6.9796], fluid composite score (p = 0.03, effect size (d) = -4.438 [-0.406, -8.47], and picture vocabulary score (p = 0.04, effect size (d) = -3.7499 [-0.0617, -7.438]. Our results showed that cortical thickness could be a candidate neuroimaging biomarker for cancer-related cognitive impairment and accelerated aging in older long-term cancer survivors.

Association of Regional Cortical Network Atrophy With Progression to Dementia in Patients With Primary Progressive Aphasia

BACKGROUND AND OBJECTIVES

Patients with primary progressive aphasia (PPA) have gradually progressive language deficits during the initial phase of the illness. As the underlying neurodegenerative disease progresses, patients with PPA start losing independent functioning due to the development of nonlanguage cognitive or behavioral symptoms. The timeline of this progression from the mild cognitive impairment stage to the dementia stage of PPA is variable across patients. In this study, in a sample of patients with PPA, we measured the magnitude of cortical atrophy within functional networks believed to subserve diverse cognitive and affective functions. The objective of the study was to evaluate the utility of this measure as a predictor of time to subsequent progression to dementia in PPA.

METHODS

Patients with PPA with largely independent daily function were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit. All patients underwent an MRI scan at baseline. Cortical atrophy was then estimated relative to a group of amyloid-negative cognitively normal control participants. For each patient, we measured the time between the baseline visit and the subsequent visit at which dementia progression was documented or last observation. Simple and multivariable Cox regression models were used to examine the relationship between cortical atrophy and the likelihood of progression to dementia.

RESULTS

Forty-nine patients with PPA (mean age = 66.39 ± 8.36 years, 59.2% females) and 25 controls (mean age = 67.43 ± 4.84 years, 48% females) were included in the data analysis. Greater baseline atrophy in not only the left language network (hazard ratio = 1.47, 95% CI = 1.17-1.84) but also in the frontoparietal control (1.75, 1.25-2.44), salience (1.63, 1.25-2.13), default mode (1.55, 1.19-2.01), and ventral frontotemporal (1.41, 1.16-1.71) networks was associated with a higher risk of progression to dementia. A multivariable model identified contributions of the left frontoparietal control (1.94, 1.09-3.48) and ventral frontotemporal (1.61, 1.09-2.39) networks in predicting dementia progression, with no additional variance explained by the language network (0.75, 0.43-1.31).

DISCUSSION

These results suggest that baseline atrophy in cortical networks subserving nonlanguage cognitive and affective functions is an important predictor of progression to dementia in PPA. This measure should be included in precision medicine models of prognosis in PPA.

Early Amnestic Mild Cognitive Impairment Is Associated with Reduced Total Cerebral Blood Flow with no Brain Tissue Loss

BACKGROUND

Lower cerebral blood flow (CBF) and excessive brain atrophy are linked to Alzheimer's disease (AD). It is still undetermined whether reduced CBF precedes or follows brain tissue loss.

OBJECTIVE

We compared total CBF (tCBF), global cerebral perfusion (GCP), and volumes of AD-prone regions between cognitively normal (CN) and early amnestic mild cognitive impairment (aMCI) and tested their associations with cognitive performance to assess their predictive value for differentiation between CN and early aMCI.

METHODS

A total of 74 participants (mean age 69.9±6.2 years, 47 females) were classified into two groups: 50 CN and 24 aMCI, of whom 88% were early aMCI. tCBF, GCP, and global and regional brain volumetry were measured using phase-contrast and T1-weighted MRI. Neuropsychological tests tapping global cognition and four cognitive domains (memory, executive function, language, and visuospatial) were administered. Comparisons and associations were investigated using analyses of covariance (ANCOVA) and linear regression analyses, respectively.

RESULTS

Women had significantly higher GCP than men. Both, tCBF and GCP were significantly reduced in aMCI compared with CN, while differences in volumes of cerebral gray matter, white matter, and AD-prone regions were not significant. tCBF and GCP were significantly associated with global cognition (standardized beta (stβ) = 0.324 and stβ= 0.326) and with memory scores (stβ≥0.297 and stβ≥0.264) across all participants. Associations of tCBF and GCP with memory scores were also significant in CN (stβ= 0.327 and stβ= 0.284) and in aMCI (stβ= 0.627 and stβ= 0.485).

CONCLUSION

Reduced tCBF and GCP are sensitive biomarkers of early aMCI that likely precede brain tissue loss.

Early-onset Alzheimer's disease with depression as the first symptom: a case report with literature review

Background

Alzheimer's disease is a common neurodegenerative disease, and patients with early-onset Alzheimer's disease (onset age < 65 years) often have atypical symptoms, which are easily misdiagnosed and missed. Multimodality neuroimaging has become an important diagnostic and follow-up method for AD with its non-invasive and quantitative advantages.

Case presentation

We report a case of a 59-year-old female with a diagnosis of depression at the age of 50 after a 46-year-old onset and a 9-year follow-up observation, who developed cognitive dysfunction manifested by memory loss and disorientation at the age of 53, and eventually developed dementia. Combined with neuropsychological scales (MMSE and MOCA scores decreased year by year and finally reached the dementia criteria) and the application of multimodal imaging. MRI showed that the hippocampus atrophied year by year and the cerebral cortex was extensively atrophied. 18F-FDG PET image showed hypometabolism in right parietal lobes, bilateral frontal lobes, bilateral joint parieto-temporal areas, and bilateral posterior cingulate glucose metabolism. The 18F-AV45 PET image showed the diagnosis of early-onset Alzheimer's disease was confirmed by the presence of Aβ deposits in the cerebral cortex.

Conclusion

Early-onset Alzheimer's disease, which starts with depression, often has atypical symptoms and is prone to misdiagnosis. The combination of neuropsychological scales and neuroimaging examinations are good screening tools that can better assist in the early diagnosis of Alzheimer's disease. Graphical Abstract.

Multimodal Machine Learning for 10-Year Dementia Risk Prediction: The Framingham Heart Study

BACKGROUND

Early prediction of dementia risk is crucial for effective interventions. Given the known etiologic heterogeneity, machine learning methods leveraging multimodal data, such as clinical manifestations, neuroimaging biomarkers, and well-documented risk factors, could predict dementia more accurately than single modal data.

OBJECTIVE

This study aims to develop machine learning models that capitalize on neuropsychological (NP) tests, magnetic resonance imaging (MRI) measures, and clinical risk factors for 10-year dementia prediction.

METHODS

This study included participants from the Framingham Heart Study, and various data modalities such as NP tests, MRI measures, and demographic variables were collected. CatBoost was used with Optuna hyperparameter optimization to create prediction models for 10-year dementia risk using different combinations of data modalities. The contribution of each modality and feature for the prediction task was also quantified using Shapley values.

RESULTS

This study included 1,031 participants with normal cognitive status at baseline (age 75±5 years, 55.3% women), of whom 205 were diagnosed with dementia during the 10-year follow-up. The model built on three modalities demonstrated the best dementia prediction performance (AUC 0.90±0.01) compared to single modality models (AUC range: 0.82-0.84). MRI measures contributed most to dementia prediction (mean absolute Shapley value: 3.19), suggesting the necessity of multimodal inputs.

CONCLUSION

This study shows that a multimodal machine learning framework had a superior performance for 10-year dementia risk prediction. The model can be used to increase vigilance for cognitive deterioration and select high-risk individuals for early intervention and risk management.

Brain Aging Among Racially and Ethnically Diverse Middle-Aged and Older Adults

Importance

Neuroimaging studies have documented racial and ethnic disparities in brain health in old age. It remains unclear whether these disparities are apparent in midlife.

Objective

To assess racial and ethnic disparities in magnetic resonance imaging (MRI) markers of cerebrovascular disease and neurodegeneration in midlife and late life.

Design, Setting, and Participants

Data from 2 community-based cohort studies, Washington Heights-Inwood Columbia Aging Project (WHICAP) and the Offspring Study of Racial and Ethnic Disparities in Alzheimer Disease (Offspring), were used. Enrollment took place from March 2011 and June 2017, in WHICAP and Offspring, respectively, to January 2021. Of the 822 Offspring and 1254 WHICAP participants approached for MRI scanning, 285 and 176 refused participation in MRI scanning, 36 and 76 were excluded for contraindications/ineligibility, and 4 and 32 were excluded for missing key variables, respectively.

Main Outcomes and Measures

Cortical thickness in Alzheimer disease-related regions, white matter hyperintensity (WMH) volume.

Results

The final sample included 1467 participants. Offspring participants (497 [33.9%]) had a mean (SD) age of 55 (10.7) years, had a mean (SD) of 13 (3.5) years of education, and included 117 Black individuals (23.5%), 348 Latinx individuals (70%), 32 White individuals (6.4%), and 324 women (65.2%). WHICAP participants (970 [66.1%]) had a mean (SD) age of 75 (6.5) years, had a mean (SD) of 12 (4.7) years of education, and included 338 Black individuals (34.8%), 389 Latinx individuals (40.1%), 243 White individuals (25.1%), and 589 women (65.2%). Racial and ethnic disparities in cerebrovascular disease were observed in both midlife (Black-White: B = 0.357; 95% CI, 0.708-0.007; P = .046) and late life (Black-Latinx: B = 0.149, 95% CI, 0.068-0.231; P < .001; Black-White: B = 0.166; 95% CI, 0.254-0.077; P < .001), while disparities in cortical thickness were evident in late life only (Black-Latinx: B = -0.037; 95% CI, -0.055 to -0.019; P < .001; Black-White: B = -0.064; 95% CI -0.044 to -0.084; P < .001). Overall, Black-White disparities were larger than Latinx-White disparities for cortical thickness and WMH volume. Brain aging, or the association of age with MRI measures, was greater in late life compared with midlife for Latinx (cortical thickness: B = 0.006; 95% CI, 0.004-0.008; P < .001; WMH volume: B = -0.010; 95% CI, -0.018 to -0.001; P = .03) and White (cortical thickness: B = 0.005; 95% CI, 0.002-0.008; P = .001; WMH volume: B = -0.021; 95% CI -0.043 to 0.002; P = .07) participants but not Black participants (cortical thickness: B = 0.001; 95% CI, -0.002 to 0.004; P =.64; WMH volume: B = 0.003; 95% CI, -0.010 to 0.017; P = .61), who evidenced a similarly strong association between age and MRI measures in midlife and late life.

Conclusions and Relevance

In this study, racial and ethnic disparities in small vessel cerebrovascular disease were apparent in midlife. In Latinx and White adults, brain aging was more pronounced in late life than midlife, whereas Black adults showed accelerated pattern of brain aging beginning in midlife.

Machine Learning-Based Classification of Subjective Cognitive Decline, Mild Cognitive Impairment, and Alzheimer's Dementia Using Neuroimage and Plasma Biomarkers

Alzheimer's disease (AD) progresses relentlessly from the preclinical to the dementia stage. The process begins decades before the diagnosis of dementia. Therefore, it is crucial to detect early manifestations to prevent cognitive decline. Recent advances in artificial intelligence help tackle the complex high-dimensional data encountered in clinical decision-making. In total, we recruited 206 subjects, including 69 cognitively unimpaired, 40 subjective cognitive decline (SCD), 34 mild cognitive impairment (MCI), and 63 AD dementia (ADD). We included 3 demographic, 1 clinical, 18 brain-image, and 3 plasma biomarker (Aß_1-42, Aß_1-40, and tau protein) features. We employed the linear discriminant analysis method for feature extraction to make data more distinguishable after dimension reduction. The sequential forward selection method was used for feature selection to identify the 12 best features for machine learning classifiers. We used both random forest and support vector machine as classifiers. The area under the receiver operative curve (AUROC) was close to 0.9 between diseased (combining ADD and MCI) and the controls. AUROC was higher than 0.85 between SCD and controls, 0.90 between MCI and SCD, and above 0.85 between ADD and MCI. We can differentiate between adjacent phases of the AD spectrum with blood biomarkers and brain MR images with the help of machine learning algorithms.

Semantic intrusion errors as a function of age, amyloid, and volumetric loss: a confirmatory path analysis

OBJECTIVE

To examine the direct and indirect effects of age, APOE ϵ4 genotype, amyloid positivity, and volumetric reductions in AD-prone brain regions as it relates to semantic intrusion errors reflecting proactive semantic interference (PSI) and the failure to recover from proactive semantic interference (frPSI) on the Loewenstein-Acevedo Scales of Semantic Interference and Learning (LASSI-L), a cognitive stress test that has been consistently more predictive of preclinical and prodromal Alzheimer's disease (AD) than traditional list-learning tests.

DESIGN

Cross-sectional study.

SETTING

1Florida Alzheimer's Disease Research Center baseline study.

PARTICIPANTS

Two-hundred and twelve participants with Mini-Mental State Examination (MMSE) score above 16 and a broad array of cognitive diagnoses ranging from cognitively normal (CN) to dementia, of whom 58% were female, mean age of 72.1 (SD 7.9).

MEASURES

Participants underwent extensive clinical and neuropsychological evaluations, MR and amyloid Positron Emission Tomography/Computer/Computer Tomography (PET/CT) imaging, and analyses of APOE ϵ4 genotype. Confirmatory path analyses were conducted in the structural equation modeling framework that estimated multiple equations simultaneously while controlling for important covariates such as sex, education, language of evaluation, and global cognitive impairment.

RESULTS

Both amyloid positivity and decreased brain volumes in AD-prone regions were directly related to LASSI-L Cued B1 and Cued B2 intrusions (sensitive to PSI and frPSI effects) even after controlling for covariates. APOE ϵ4 status did not evidence direct effects on these LASSI-L cognitive markers, but rather exerted their effects on amyloid positivity, which in turn related to PSI and frPSI. Similarly, age did not have a direct relationship with LASSI-L scores, but exerted its effects indirectly through amyloid positivity and volumes of AD-prone brain regions.

CONCLUSIONS

Our study provides insight into the relationships among age, APOE ϵ4, amyloid, and brain volumetric reductions as it relates to semantic intrusion errors. The investigation expands our understanding of the underpinnings of PSI and frPSI intrusions in a large cohort.

Metacognition, cortical thickness, and tauopathy in aging

We investigated self-rating of cognitive task performance (self-appraisal) and the difference between self-rating and actual task performance (appraisal discrepancy) in cognitively healthy older adults and their relationship with cortical thickness and Alzheimer's disease (AD) biomarkers, amyloid and tau. All participants (N = 151) underwent neuropsychological testing and 1.5T structural magnetic resonance imaging. A subset (N = 66) received amyloid-PET with [11C] PiB and tau-PET with [18F] Flortaucipir. We found that worse performers had lower self-appraisal ratings, but still overestimated their performance, consistent with the Dunning-Kruger effect. Self-appraisal rating and appraisal discrepancy revealed distinct relationships with cortical thickness and AD pathology. Greater appraisal discrepancy, indicating overestimation, was related to thinning of inferior-lateral temporal, fusiform, and rostral anterior cingulate cortices. Lower self-appraisal was associated with higher entorhinal and inferior temporal tau. These results suggest that overestimation could implicate structural atrophy beyond AD pathology, while lower self-appraisal could indicate early behavioral alteration due to AD pathology, supporting the notion of subjective cognitive decline prior to objective deficits.

Cognitive dispersion is elevated in amyloid-positive older adults and associated with regional hypoperfusion

OBJECTIVE

Cognitive dispersion across neuropsychological measures within a single testing session is a promising marker predictive of cognitive decline and development of Alzheimer's disease (AD). However, little is known regarding brain changes underlying cognitive dispersion, and the association of cognitive dispersion with in vivo AD biomarkers and regional cerebral blood flow (CBF) has received limited study. We therefore examined associations among cognitive dispersion, amyloid-beta (Aβ) positivity, and regional CBF among older adults free of dementia.

METHOD

One hundred and forty-eight Alzheimer's Disease Neuroimaging Initiative (ADNI) participants underwent neuropsychological testing and neuroimaging. Pulsed arterial spin labeling (ASL) magnetic resonance imaging (MRI) was acquired to quantify CBF. Florbetapir positron emission tomography (PET) imaging determined Aβ positivity.

RESULTS

Adjusting for age, gender, education, and mean cognitive performance, older adults who were Aβ+ showed higher cognitive dispersion relative to those who were Aβ-. Across the entire sample, higher cognitive dispersion was associated with reduced CBF in inferior parietal and temporal regions. Secondary analyses stratified by Aβ status demonstrated that higher cognitive dispersion was associated with reduced CBF among Aβ+ individuals but not among those who were Aβ-.

CONCLUSIONS

Cognitive dispersion may be sensitive to early Aβ accumulation and cerebrovascular changes adjusting for demographics and mean neuropsychological performance. Associations between cognitive dispersion and CBF were observed among Aβ+ individuals, suggesting that cognitive dispersion may be a marker of brain changes among individuals on the AD continuum. Future studies should examine whether cognitive dispersion predicts brain changes in diverse samples and among those with greater vascular risk burden.

Longitudinal change in serial position scores in older adults with entorhinal and hippocampal neuropathologies

OBJECTIVE

Serial position scores on verbal memory tests are sensitive to early Alzheimer's disease (AD)-related neuropathological changes that occur in the entorhinal cortex and hippocampus. The current study examines longitudinal change in serial position scores as markers of subtle cognitive decline in older adults who may be in preclinical or at-risk states for AD.

METHODS

This study uses longitudinal data from the Religious Orders Study and the Rush Memory and Aging Project. Participants (n = 141) were included if they did not have dementia at enrollment, completed follow-up assessments, and died and were classified as Braak stage I or II. Memory tests were used to calculate serial position (primacy, recency), total recall, and episodic memory composite scores. A neuropathological evaluation quantified AD, vascular, and Lewy body pathologies. Mixed effects models were used to examine change in memory scores. Neuropathologies and covariates (age, sex, education, APOE e4) were examined as moderators.

RESULTS

Primacy scores declined (β = -.032, p < .001), whereas recency scores increased (β = .021, p = .012). No change was observed in standard memory measures. Greater neurofibrillary tangle density and atherosclerosis explained 10.4% of the variance in primacy decline. Neuropathologies were not associated with recency change.

CONCLUSIONS

In older adults with hippocampal neuropathologies, primacy score decline may be a sensitive marker of early AD-related changes. Tangle density and atherosclerosis had additive effects on decline. Recency improvement may reflect a compensatory mechanism. Monitoring for changes in serial position scores may be a useful in vivo method of tracking incipient AD.

Amyloid, cerebrovascular disease, and neurodegeneration biomarkers are associated with cognitive trajectories in a racially and ethnically diverse, community-based sample

We characterized the additive contribution of cerebrovascular biomarkers to amyloid and neurodegeneration biomarkers (AV(N)) when modeling prospective, longitudinal cognitive trajectories within 3 major racial/ethnic groups. Participants (n = 172; age = 69-96 years; 62% women; 31%/49%/20% Non-Hispanic White/Non-Hispanic Black/Hispanic) from the Washington Heights-Inwood Columbia Aging Project were assessed for amyloid (Florbetaben PET), neurodegeneration (cortical thickness, hippocampal volume), and cerebrovascular disease (white matter hyperintensity (WMH), infarcts). Neuropsychological assessments occurred every 2.3 ± 0.6 years for up to 6 visits (follow-up time: 4.2 ± 3.2 years). Linear mixed-effects models were stratified by race/ethnicity groups. Higher amyloid was associated with faster memory decline in all 3 racial/ethnic groups, but was related to faster cognitive decline beyond memory in minoritized racial/ethnic groups. Higher WMH was associated with faster language, processing speed/executive function, and visuospatial ability decline in Non-Hispanic Black participants, while infarcts were associated with faster processing speed/executive function decline in Non-Hispanic White participants. Complementary information from AD, neurodegenerative, and cerebrovascular biomarkers explain decline in multiple cognitive domains, which may differ within each racial/ethnic group. Importantly, treatment strategies exist to minimize vascular contributions to cognitive decline.

Brain-age is associated with progression to dementia in memory clinic patients

BACKGROUND

Biomarkers for the early detection of dementia risk hold promise for better disease monitoring and targeted interventions. However, most biomarker studies, particularly in neuroimaging, have analysed artificially 'clean' research groups, free from comorbidities, erroneous referrals, contraindications and from a narrow sociodemographic pool. Such biases mean that neuroimaging samples are often unrepresentative of the target population for dementia risk (e.g., people referred to a memory clinic), limiting the generalisation of these studies to real-world clinical settings. To facilitate better translation from research to the clinic, datasets that are more representative of dementia patient groups are warranted.

METHODS

We analysed T1-weighted MRI scans from a real-world setting of patients referred to UK memory clinic services (n = 1140; 60.2 % female and mean [SD] age of 70.0[10.8] years) to derive 'brain-age'. Brain-age is an index of age-related brain health based on quantitative analysis of structural neuroimaging, largely reflecting brain atrophy. Brain-predicted age difference (brain-PAD) was calculated as brain-age minus chronological age. We determined which patients went on to develop dementia between three months and 7.8 years after neuroimaging assessment (n = 476) using linkage to electronic health records.

RESULTS

Survival analysis, using Cox regression, indicated a 3 % increased risk of dementia per brain-PAD year (hazard ratio [95 % CI] = 1.03 [1.02,1.04], p < 0.0001), adjusted for baseline age, age2, sex, Mini Mental State Examination (MMSE) score and normalised brain volume. In sensitivity analyses, brain-PAD remained significant when time-to-dementia was at least 3 years (hazard ratio [95 % CI] = 1.06 [1.02, 1.09], p = 0.0006), or when baseline MMSE score ≥ 27 (hazard ratio [95 % CI] = 1.03 [1.01, 1.05], p = 0.0006).

CONCLUSIONS

Memory clinic patients with older-appearing brains are more likely to receive a subsequent dementia diagnosis. Potentially, brain-age could aid decision-making during initial memory clinic assessment to improve early detection of dementia. Even when neuroimaging assessment was more than 3 years prior to diagnosis and when cognitive functioning was not clearly impaired, brain-age still proved informative. These real-world results support the use of quantitative neuroimaging biomarkers like brain-age in memory clinics.

Detection of emerging neurodegeneration using Bayesian linear mixed-effect modeling

Early detection of neurodegeneration, and prediction of when neurodegenerative diseases will lead to symptoms, are critical for developing and initiating disease modifying treatments for these disorders. While each neurodegenerative disease has a typical pattern of early changes in the brain, these disorders are heterogeneous, and early manifestations can vary greatly across people. Methods for detecting emerging neurodegeneration in any part of the brain are therefore needed. Prior publications have described the use of Bayesian linear mixed-effects (BLME) modeling for characterizing the trajectory of change across the brain in healthy controls and patients with neurodegenerative disease. Here, we use an extension of such a model to detect emerging neurodegeneration in cognitively healthy individuals at risk for dementia. We use BLME to quantify individualized rates of volume loss across the cerebral cortex from the first two MRIs in each person and then extend the BLME model to predict future values for each voxel. We then compare observed values at subsequent time points with the values that were expected from the initial rates of change and identify voxels that are lower than the expected values, indicating accelerated volume loss and neurodegeneration. We apply the model to longitudinal imaging data from cognitively normal participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI), some of whom subsequently developed dementia, and two cognitively normal cases who developed pathology-proven frontotemporal lobar degeneration (FTLD). These analyses identified regions of accelerated volume loss prior to or accompanying the earliest symptoms, and expanding across the brain over time, in all cases. The changes were detected in regions that are typical for the likely diseases affecting each patient, including medial temporal regions in patients at risk for Alzheimer's disease, and insular, frontal, and/or anterior/inferior temporal regions in patients with likely or proven FTLD. In the cases where detailed histories were available, the first regions identified were consistent with early symptoms. Furthermore, survival analysis in the ADNI cases demonstrated that the rate of spread of accelerated volume loss across the brain was a statistically significant predictor of time to conversion to dementia. This method for detection of neurodegeneration is a potentially promising approach for identifying early changes due to a variety of diseases, without prior assumptions about what regions are most likely to be affected first in an individual.

Adenosine receptor signalling in Alzheimer’s disease

Alzheimer’s disease (AD) is the most common dementia in the elderly and its increasing prevalence presents treatment challenges. Despite a better understanding of the disease, the current mainstay of treatment cannot modify pathogenesis or effectively address the associated cognitive and memory deficits. Emerging evidence suggests adenosine G protein-coupled receptors (GPCRs) are promising therapeutic targets for Alzheimer’s disease. The adenosine A₁ and A_2A receptors are expressed in the human brain and have a proposed involvement in the pathogenesis of dementia. Targeting these receptors preclinically can mitigate pathogenic β-amyloid and tau neurotoxicity whilst improving cognition and memory. In this review, we provide an accessible summary of the literature on Alzheimer’s disease and the therapeutic potential of A₁ and A_2A receptors. Although there are no available medicines targeting these receptors approved for treating dementia, we provide insights into some novel strategies, including allosterism and the targeting of oligomers, which may increase drug discovery success and enhance the therapeutic response.

Longitudinal Intraindividual Cognitive Variability Is Associated With Reduction in Regional Cerebral Blood Flow Among Alzheimer's Disease Biomarker-Positive Older Adults

Intraindividual variability (IIV) across neuropsychological measures within a single testing session is a promising marker predictive of cognitive decline and development of Alzheimer's disease (AD). We have previously shown that greater IIV is cross-sectionally associated with reduced cerebral blood flow (CBF), but not with cortical thickness or brain volume, in older adults without dementia who were amyloid beta (Aβ) positive. However, there is little known about the association between change in IIV and CBF over time. Therefore, we examined 12-month longitudinal change in IIV and interactions of IIV and AD biomarker status on changes in regional CBF. Fifty-three non-demented Alzheimer's Disease Neuroimaging Initiative (ADNI) participants underwent lumbar puncture to obtain cerebrospinal fluid (CSF) at baseline and neuropsychological testing and magnetic resonance imaging (MRI) exams at baseline and 12-month follow-up evaluation. IIV was calculated as the intraindividual standard deviation across 6 demographically-corrected neuropsychological measures. Pulsed arterial spin labeling (ASL) MRI was acquired to quantify CBF and FreeSurfer-derived a priori CBF regions of interest (ROIs) were examined. AD biomarker positivity was determined using a published CSF p-tau/Aβ ratio cut-score. Change scores were calculated for IIV, CBF, and mean neuropsychological performance from baseline to 12 months. Hierarchical linear regression models showed that after adjusting for age and gender, there was a significant interaction between IIV change and biomarker-positivity (p-tau/Aβ+) for change in entorhinal and hippocampal CBF but not for the other ROIs. Specifically, increases in IIV were associated with reductions in entorhinal and hippocampal CBF among individuals who were biomarker-positive (n = 21). In contrast, there were no significant associations between change in IIV and CBF among those who were biomarker-negative (n = 32). Findings remained similar when analyses were performed adjusting for change in mean level of neuropsychological performance. Changes in IIV may be sensitive to changes in regional hypoperfusion in AD-vulnerable regions among AD biomarker-positive individuals, above and beyond demographics and mean neuropsychological performance. These findings provide further evidence supporting IIV as a potential marker of cerebrovascular brain changes in individuals at risk for dementia.

Structural integrity of the anterior mid-cingulate cortex contributes to resilience to delirium in SuperAging

Despite its devastating clinical and societal impact, approaches to treat delirium in older adults remain elusive, making it important to identify factors that may confer resilience to this syndrome. Here, we investigated a cohort of 93 cognitively normal older patients undergoing elective surgery recruited as part of the Successful Aging after Elective Surgery study. Each participant was classified either as a SuperAger (n = 19) or typically aging older adult (n = 74) based on neuropsychological criteria, where the former was defined as those older adults whose memory function rivals that of young adults. We compared these subgroups to examine the role of preoperative memory function in the incidence and severity of postoperative delirium. We additionally investigated the association between indices of postoperative delirium symptoms and cortical thickness in functional networks implicated in SuperAging based on structural magnetic resonance imaging data that were collected preoperatively. We found that SuperAging confers the real-world benefit of resilience to delirium, as shown by lower (i.e. zero) incidence of postoperative delirium and decreased severity scores compared with typical older adults. Furthermore, greater baseline cortical thickness of the anterior mid-cingulate cortex—a key node of the brain’s salience network that is also consistently implicated in SuperAging—predicted lower postoperative delirium severity scores in all patients. Taken together, these findings suggest that baseline memory function in older adults may be a useful predictor of postoperative delirium risk and severity and that superior memory function may contribute to resilience to delirium. In particular, the integrity of the anterior mid-cingulate cortex may be a potential biomarker of resilience to delirium, pointing to this region as a potential target for preventive or therapeutic interventions designed to mitigate the risk or consequences of developing this prevalent clinical syndrome.

Associations of vascular risk and amyloid burden with subsequent dementia

OBJECTIVE

Midlife vascular risk factors (MVRF) are associated with incident dementia, as are amyloid β(Aβ) deposition and neurodegeneration. Whether vascular and Alzheimer Disease (AD)-associated factors contribute to dementia independently or interact synergistically to reduce cognition is poorly understood.

METHODS

Participants in the Atherosclerosis Risk in Communities (ARIC)-PET study were followed from 1987-89(45-64 yo) through 2016-17(74-94 yo), with repeat cognitive assessment and dementia adjudication. In 2011-13, dementia-free participants underwent brain MRI (with white matter hyperintensity (WMH) and brain volume measurement) and florbetapir (Aβ) PET. The relative contributions of vascular risk and injury (MVRF, WMH volume), elevated Aβ standardized uptake value ratio (SUVR), and neurodegeneration (smaller temporo-parietal brain regions) to incident dementia were evaluated with adjusted Cox models.

RESULTS

In 298 individuals, 36 developed dementia (median follow-up 4.9 years). Midlife hypertension and Aβ each independently predicted dementia risk (hypertension:HR 2.57 (95% CI 1.16-5.67); Aβ SUVR(per SD):HR 2.57 (1.72-3.84)), but didn't interact significantly, whereas late-life diabetes (HR 2.50 (1.18 to 5.28)) and Aβ independently predicted dementia risk. WMH(per SD):HR 1.51 (1.03-2.20) and Aβ SUVR (HR 2.52 (1.83-3.47)) independently contributed to incident dementia but WMH lost significance when MVRF were included. Smaller temporo-parietal brain regions were associated with incident dementia, independent of Aβ and MVRF (HR 2.18 (1.18-4.01)).

INTERPRETATION

Midlife hypertension and late-life Aβ are independently associated with dementia risk, without evidence for synergy on a multiplicative scale. Given the independent contributions of vascular and amyloid mechanisms, multiple pathways should be considered when evaluating interventions to reduce the burden of dementia. This article is protected by copyright. All rights reserved.

Neuroimaging Modalities in Alzheimer’s Disease: Diagnosis and Clinical Features

Alzheimer’s disease (AD) is a neurodegenerative disease causing progressive cognitive decline until eventual death. AD affects millions of individuals worldwide in the absence of effective treatment options, and its clinical causes are still uncertain. The onset of dementia symptoms indicates severe neurodegeneration has already taken place. Therefore, AD diagnosis at an early stage is essential as it results in more effective therapy to slow its progression. The current clinical diagnosis of AD relies on mental examinations and brain imaging to determine whether patients meet diagnostic criteria, and biomedical research focuses on finding associated biomarkers by using neuroimaging techniques. Multiple clinical brain imaging modalities emerged as potential techniques to study AD, showing a range of capacity in their preciseness to identify the disease. This review presents the advantages and limitations of brain imaging modalities for AD diagnosis and discusses their clinical value.

Cultural factors related to neuropsychological performance and brain atrophy among Hispanic older adults with amnestic Mild Cognitive Impairment (aMCI): A pilot study

OBJECTIVES

This study examined the association of cultural factors and literacy to neuropsychological performance and measures of regional brain atrophy among Hispanic elders diagnosed with amnestic Mild Cognitive Impairment (aMCI).

METHOD

Acculturation and literacy levels were measured among 45 subjects tested in Spanish; their primary language. Scores for measures of memory, executive functioning, and verbal fluency, as well as volumetric analysis of MRI scans of left hemisphere structures commonly affected by Alzheimer's disease (AD) were examined. Linear regression models were employed to examine the association of acculturation and literacy to neuropsychological performance and MRI measures.

RESULTS

After controlling for age, higher literacy levels were associated with better performance on phonemic verbal fluency (r = 0.300, p < .05), while higher levels of acculturation to the U.S. was associated with poorer performance on category verbal fluency (r = 0.300, p < .05). There was a significant inverse relationship after controlling for age between literacy and the left entorhinal cortex (r = -0.455, p < .05), left precuneus (r = -0.457, p < .05), and left posterior cingulate (r = -0.415, p < .05).

CONCLUSIONS

Results of the current pilot study indicate that high acculturation to the U.S. among aMCI immigrants from Latin-American countries may hinder performance on verbal learning measures when they are administered in one's primary language. Moreover, in this cohort, a higher literacy level, which is indicative of greater cognitive reserve, was associated with better performance in language measures, but with greater atrophy in brain regions susceptible to neurodegenerative disease. These preliminary findings should be further examined among larger cohorts and using more diverse measures, which capture other cultural constructs.