Neuromodulatory subcortical nucleus integrity is associated with white matter microstructure, tauopathy and APOE status.

The neuromodulatory subcortical nuclei within the isodendritic core (IdC) are the earliest sites of tauopathy in Alzheimer's disease (AD). They project broadly throughout the brain's white matter. We investigated the relationship between IdC microstructure and whole-brain white matter microstructure to better understand early neuropathological changes in AD. Using multiparametric quantitative magnetic resonance imaging we observed two covariance patterns between IdC and white matter microstructure in 133 cognitively unimpaired older adults (age 67.9 ± 5.3 years) with familial risk for AD. IdC integrity related to 1) whole-brain neurite density, and 2) neurite orientation dispersion in white matter tracts known to be affected early in AD. Pattern 2 was associated with CSF concentration of phosphorylated-tau, indicating AD specificity. Apolipoprotein-E4 carriers expressed both patterns more strongly than non-carriers. IdC microstructure variation is reflected in white matter, particularly in AD-affected tracts, highlighting an early mechanism of pathological development.

Locus coeruleus integrity is related to an exploitation-based decision-making bias in older adulthood.

Optimal decision-making balances exploration for new information against exploitation of known rewards, a process mediated by the locus coeruleus and its norepinephrine projections. We predicted that an exploitation-bias that emerges in older adulthood would be associated with lower microstructural integrity of the locus coeruleus. Leveraging in vivo histological methods from quantitative MRI-magnetic transfer saturation-we provide evidence that older age is associated with lower locus coeruleus integrity. Critically, we demonstrate that an exploitation bias in older adulthood, assessed with a foraging task, is sensitive and specific to lower locus coeruleus integrity. Because the locus coeruleus is uniquely vulnerable to Alzheimer's disease pathology, our findings suggest that aging, and a presymptomatic trajectory of Alzheimer's related decline, may fundamentally alter decision-making abilities in later life.

Genetics impact risk of Alzheimer's disease through mechanisms modulating structural brain morphology in late life.

BACKGROUND: Alzheimer's disease (AD)-related neuropathological changes can occur decades before clinical symptoms. We aimed to investigate whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or increasing brain atrophy, respectively. METHODS: We used bidirectional two-sample Mendelian randomisation to estimate the effects between genetic liability to AD and global and regional cortical thickness, estimated total intracranial volume, volume of subcortical structures and total white matter in 37 680 participants aged 8-81 years across 5 independent cohorts (Adolescent Brain Cognitive Development, Generation R, IMAGEN, Avon Longitudinal Study of Parents and Children and UK Biobank). We also examined the effects of global and regional cortical thickness and subcortical volumes from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium on AD risk in up to 37 741 participants. RESULTS: Our findings show that AD risk alleles have an age-dependent effect on a range of cortical and subcortical brain measures that starts in mid-life, in non-clinical populations. Evidence for such effects across childhood and young adulthood is weak. Some of the identified structures are not typically implicated in AD, such as those in the striatum (eg, thalamus), with consistent effects from childhood to late adulthood. There was little evidence to suggest brain morphology alters AD risk. CONCLUSIONS: Genetic liability to AD is likely to affect risk of AD primarily through mechanisms affecting indicators of brain morphology in later life, rather than structural brain reserve. Future studies with repeated measures are required for a better understanding and certainty of the mechanisms at play.

Sleep quality during and after severe acute respiratory syndrome coronavirus 2 (COVID-19) lockdowns in the UK: Results from the SleepQuest study.

Sleep is fundamental to health. The aim of this study was to analyse and determine factors predicting sleep quality during and after national lockdowns due to severe acute respiratory syndrome coronavirus 2 (COVID-19) in the UK. A longitudinal online survey-based study (SleepQuest) involving UK adults was administered in Spring 2020, Winter 2020, and Winter 2022 including questionnaires probing sleep quality, depression, anxiety, beliefs about sleep, demographics, COVID-19 status, and exercise. The primary outcome was sleep quality (Pittsburgh Sleep Quality Index). A linear mixed-effects model evaluated factors associated with baseline and longitudinal sleep quality. Complete data were provided by 3306 participants in Spring 2020, 2196 participants in Winter 2020, and 1193 in Winter 2022. Participants were mostly female (73.8%), white (97.4%), and aged over 50 years (81.0%). On average, participants reported poor sleep quality in Spring 2020 (mean [SD] Pittsburgh Sleep Quality Index score = 6.59 [3.6]) and Winter 2020 (mean [SD] Pittsburgh Sleep Quality Index score = 6.44 [3.6]), with improved but still poor sleep quality in Winter 2022 (mean [SD] Pittsburgh Sleep Quality Index score = 6.17 [3.5]). Improved sleep quality was driven by better subjective sleep and reduced daytime dysfunction and sleep latency. Being female, older, having caring responsibilities, working nightshifts, and reporting higher levels of depression, anxiety, and unhelpful beliefs about sleep were associated with worse baseline PSQI scores. Better sleep quality was associated with more days exercising per week at baseline. Interventions focusing on improving mental health, exercise, and attitudes towards sleep, particularly in at-risk groups, may improve sleep-related outcomes in future pandemics.

Iron Deposition and Distribution Across the Hippocampus Is Associated with Pattern Separation and Pattern Completion in Older Adults at Risk for Alzheimer's Disease.

Elevated iron deposition in the brain has been observed in older adult humans and persons with Alzheimer's disease (AD), and has been associated with lower cognitive performance. We investigated the impact of iron deposition, and its topographical distribution across hippocampal subfields and segments (anterior, posterior) measured along its longitudinal axis, on episodic memory in a sample of cognitively unimpaired older adults at elevated familial risk for AD (N = 172, 120 females, 52 males; mean age = 68.8 ± 5.4 years). MRI-based quantitative susceptibility maps were acquired to derive estimates of hippocampal iron deposition. The Mnemonic Similarity Task was used to measure pattern separation and pattern completion, two hippocampally mediated episodic memory processes. Greater hippocampal iron load was associated with lower pattern separation and higher pattern completion scores, both indicators of poorer episodic memory. Examination of iron levels within hippocampal subfields across its long axis revealed topographic specificity. Among the subfields and segments investigated here, iron deposition in the posterior hippocampal CA1 was the most robustly and negatively associated with the fidelity memory representations. This association remained after controlling for hippocampal volume and was observed in the context of normal performance on standard neuropsychological memory measures. These findings reveal that the impact of iron load on episodic memory performance is not uniform across the hippocampus. Both iron deposition levels as well as its spatial distribution, must be taken into account when examining the relationship between hippocampal iron and episodic memory in older adults at elevated risk for AD.

Longitudinal changes in hippocampal texture from healthy aging to Alzheimer's disease.

Early detection of Alzheimer's disease is essential to develop preventive treatment strategies. Detectible change in brain volume emerges relatively late in the pathogenic progression of disease, but microstructural changes caused by early neuropathology may cause subtle changes in the MR signal, quantifiable using texture analysis. Texture analysis quantifies spatial patterns in an image, such as smoothness, randomness and heterogeneity. We investigated whether the MRI texture of the hippocampus, an early site of Alzheimer's disease pathology, is sensitive to changes in brain microstructure before the onset of cognitive impairment. We also explored the longitudinal trajectories of hippocampal texture across the Alzheimer's continuum in relation to hippocampal volume and other biomarkers. Finally, we assessed the ability of texture to predict future cognitive decline, over and above hippocampal volume. Data were acquired from the Alzheimer's Disease Neuroimaging Initiative. Texture was calculated for bilateral hippocampi on 3T T1-weighted MRI scans. Two hundred and ninety-three texture features were reduced to five principal components that described 88% of total variance within cognitively unimpaired participants. We assessed cross-sectional differences in these texture components and hippocampal volume between four diagnostic groups: cognitively unimpaired amyloid-ß- (n = 406); cognitively unimpaired amyloid-ß+ (n = 213); mild cognitive impairment amyloid-ß+ (n = 347); and Alzheimer's disease dementia amyloid-ß+ (n = 202). To assess longitudinal texture change across the Alzheimer's continuum, we used a multivariate mixed-effects spline model to calculate a 'disease time' for all timepoints based on amyloid PET and cognitive scores. This was used as a scale on which to compare the trajectories of biomarkers, including volume and texture of the hippocampus. The trajectories were modelled in a subset of the data: cognitively unimpaired amyloid-ß- (n = 345); cognitively unimpaired amyloid-ß+ (n = 173); mild cognitive impairment amyloid-ß+ (n = 301); and Alzheimer's disease dementia amyloid-ß+ (n = 161). We identified a difference in texture component 4 at the earliest stage of Alzheimer's disease, between cognitively unimpaired amyloid-ß- and cognitively unimpaired amyloid-ß+ older adults (Cohen's d = 0.23, Padj = 0.014). Differences in additional texture components and hippocampal volume emerged later in the disease continuum alongside the onset of cognitive impairment (d = 0.30-1.22, Padj < 0.002). Longitudinal modelling of the texture trajectories revealed that, while most elements of texture developed over the course of the disease, noise reduced sensitivity for tracking individual textural change over time. Critically, however, texture provided additional information than was provided by volume alone to more accurately predict future cognitive change (d = 0.32-0.63, Padj < 0.0001). Our results support the use of texture as a measure of brain health, sensitive to Alzheimer's disease pathology, at a time when therapeutic intervention may be most effective.

L-DOPA increases slow-wave sleep duration and selectively modulates memory persistence in older adults.

Introduction: Millions of people worldwide take medications such as L-DOPA that increase dopamine to treat Parkinson's disease. Yet, we do not fully understand how L-DOPA affects sleep and memory. Our earlier research in Parkinson's disease revealed that the timing of L-DOPA relative to sleep affects dopamine's impact on long-term memory. Dopamine projections between the midbrain and hippocampus potentially support memory processes during slow wave sleep. In this study, we aimed to test the hypothesis that L-DOPA enhances memory consolidation by modulating NREM sleep. Methods: We conducted a double-blind, randomised, placebo-controlled crossover trial with healthy older adults (65-79 years, n = 35). Participants first learned a word list and were then administered long-acting L-DOPA (or placebo) before a full night of sleep. Before sleeping, a proportion of the words were re-exposed using a recognition test to strengthen memory. L-DOPA was active during sleep and the practice-recognition test, but not during initial learning. Results: The single dose of L-DOPA increased total slow-wave sleep duration by approximately 11% compared to placebo, while also increasing spindle amplitudes around slow oscillation peaks and around 1-4 Hz NREM spectral power. However, behaviourally, L-DOPA worsened memory of words presented only once compared to re-exposed words. The coupling of spindles to slow oscillation peaks correlated with these differential effects on weaker and stronger memories. To gauge whether L-DOPA affects encoding or retrieval of information in addition to consolidation, we conducted a second experiment targeting L-DOPA only to initial encoding or retrieval and found no behavioural effects. Discussion: Our results demonstrate that L-DOPA augments slow wave sleep in elderly, perhaps tuning coordinated network activity and impacting the selection of information for long-term storage. The pharmaceutical modification of slow-wave sleep and long-term memory may have clinical implications. Clinical trial registration: Eudract number: 2015-002027-26; https://doi.org/10.1186/ISRCTN90897064, ISRCTN90897064.

T2 heterogeneity as an in vivo marker of microstructural integrity in medial temporal lobe subfields in ageing and mild cognitive impairment.

A better understanding of early brain changes that precede loss of independence in diseases like Alzheimer's disease (AD) is critical for development of disease-modifying therapies. Quantitative MRI, such as T2 relaxometry, can identify microstructural changes relevant to early stages of pathology. Recent evidence suggests heterogeneity of T2 may be a more informative MRI measure of early pathology than absolute T2. Here we test whether T2 markers of brain integrity precede the volume changes we know are present in established AD and whether such changes are most marked in medial temporal lobe (MTL) subfields known to be most affected early in AD. We show that T2 heterogeneity was greater in people with mild cognitive impairment (MCI; n = 49) compared to healthy older controls (n = 99) in all MTL subfields, but this increase was greatest in MTL cortices, and smallest in dentate gyrus. This reflects the spatio-temporal progression of neurodegeneration in AD. T2 heterogeneity in CA1-3 and entorhinal cortex and volume of entorhinal cortex showed some ability to predict cognitive decline, where absolute T2 could not, however further studies are required to verify this result. Increases in T2 heterogeneity in MTL cortices may reflect localised pathological change and may present as one of the earliest detectible brain changes prior to atrophy. Finally, we describe a mechanism by which memory, as measured by accuracy and reaction time on a paired associate learning task, deteriorates with age. Age-related memory deficits were explained in part by lower subfield volumes, which in turn were directly associated with greater T2 heterogeneity. We propose that tissue with high T2 heterogeneity represents extant tissue at risk of permanent damage but with the potential for therapeutic rescue. This has implications for early detection of neurodegenerative diseases and the study of brain-behaviour relationships.

T2 heterogeneity: a novel marker of microstructural integrity associated with cognitive decline in people with mild cognitive impairment.

BACKGROUND: Early Alzheimer's disease (AD) diagnosis is vital for development of disease-modifying therapies. Prior to significant brain tissue atrophy, several microstructural changes take place as a result of Alzheimer's pathology. These include deposition of amyloid, tau and iron, as well as altered water homeostasis in tissue and some cell death. T2 relaxation time, a quantitative MRI measure, is sensitive to these changes and may be a useful non-invasive, early marker of tissue integrity which could predict conversion to dementia. We propose that different microstructural changes affect T2 in opposing ways, such that average 'midpoint' measures of T2 are less sensitive than measuring distribution width (heterogeneity). T2 heterogeneity in the brain may present a sensitive early marker of AD pathology. METHODS: In this cohort study, we tested 97 healthy older controls, 49 people with mild cognitive impairment (MCI) and 10 with a clinical diagnosis of AD. All participants underwent structural MRI including a multi-echo sequence for quantitative T2 assessment. Cognitive change over 1 year was assessed in 20 participants with MCI. T2 distributions were modelled in the hippocampus and thalamus using log-logistic distribution giving measures of log-median value (midpoint; T2µ) and distribution width (heterogeneity; T2σ). RESULTS: We show an increase in T2 heterogeneity (T2σ; p < .0001) in MCI compared to healthy controls, which was not seen with midpoint (T2µ; p = .149) in the hippocampus and thalamus. Hippocampal T2 heterogeneity predicted cognitive decline over 1 year in MCI participants (p = .018), but midpoint (p = .132) and volume (p = .315) did not. Age affects T2, but the effects described here are significant even after correcting for age. CONCLUSIONS: We show that T2 heterogeneity can identify subtle changes in microstructural integrity of brain tissue in MCI and predict cognitive decline over a year. We describe a new model that considers the competing effects of factors that both increase and decrease T2. These two opposing forces suggest that previous conclusions based on T2 midpoint may have obscured the true potential of T2 as a marker of subtle neuropathology. We propose that T2 heterogeneity reflects microstructural integrity with potential to be a widely used early biomarker of conditions such as AD.

Accelerated long-term forgetting in healthy older adults predicts cognitive decline over 1 year.

BACKGROUND: Here, we address a pivotal factor in Alzheimer's prevention-identifying those at risk early, when dementia can still be avoided. Recent research highlights an accelerated forgetting phenotype as a risk factor for Alzheimer's disease. We hypothesized that delayed recall over 4 weeks would predict cognitive decline over 1 year better than 30-min delayed recall, the current gold standard for detecting episodic memory problems which could be an early clinical manifestation of incipient Alzheimer's disease. We also expected hippocampal subfield volumes to improve predictive accuracy. METHODS: Forty-six cognitively healthy older people (mean age 70.7 ± 7.97, 21/46 female), recruited from databases such as Join Dementia Research, or a local database of volunteers, performed 3 memory tasks on which delayed recall was tested after 30 min and 4 weeks, as well as Addenbrooke's Cognitive Examination III (ACE-III) and CANTAB Paired Associates Learning. Medial temporal lobe subregion volumes were automatically measured using high-resolution 3T MRI. The ACE-III was repeated after 12 months to assess the change in cognitive ability. We used univariate linear regressions and ROC curves to assess the ability of tests of delayed recall to predict cognitive decline on ACE-III over the 12 months. RESULTS: Fifteen of the 46 participants declined over the year (≥ 3 points lost on ACE-III). Four-week verbal memory predicted cognitive decline in healthy older people better than clinical gold standard memory tests and hippocampal MRI. The best single-test predictor of cognitive decline was the 4-week delayed recall on the world list (R2 = .123, p = .018, ß = .418). Combined with hippocampal subfield volumetry, 4-week verbal recall identifies those at risk of cognitive decline with 93% sensitivity and 86% specificity (AUC = .918, p < .0001). CONCLUSIONS: We show that a test of accelerated long-term forgetting over 4 weeks can predict cognitive decline in healthy older people where traditional tests of delayed recall cannot. Accelerated long-term forgetting is a sensitive, easy-to-test predictor of cognitive decline in healthy older people. Used alone or with hippocampal MRI, accelerated forgetting probes functionally relevant Alzheimer's-related change. Accelerated forgetting will identify early-stage impairment, helping to target more invasive and expensive molecular biomarker testing.

Prospective memory in prodromal Alzheimer's disease: Real world relevance and correlations with cortical thickness and hippocampal subfield volumes.

INTRODUCTION: Prospective memory (PM) is a marker of independent living in Alzheimer's disease. PM requires cue identification (prospective component) and remembering what should happen in response to the cue (retrospective component). We assessed neuroanatomical basis and functional relevance of PM. METHODS: 84 older participants (53-94 years old, 58% male) with or without Mild Cognitive Impairment (MCI) performed PM tests, Activities of Daily Living (ADL) scale and had a structural MRI of the brain to estimate for cortical thickness and hippocampal subfield volumes. A General Linear Model cluster analysis was carried out using FreeSurfer to determine which cortical regions were correlated with PM scores. RESULTS: Both components of PM are impaired in MCI (p < .001). The retrospective component of PM correlates strongly with ADL (p = .005). Prospective component performance correlates positively with cortical thickness of bilateral frontal-temporal-parietal cortex and volume of CA1 of hippocampus. In contrast, the retrospective component performance correlates positively with cortical thickness of a right-lateralised fronto-temporal-parietal network and volumes of subiculum and CA3 hippocampal subfields. DISCUSSION: Our neuroimaging findings complement and extend previous research into structural correlates of PM. Here, we show that there are distinct, yet, overlapping brain regions correlating with the two components of PM. PM performance provides a window into real-life functional abilities in people at risk of Alzheimer's disease and could be utilised as a marker of clinically relevant disease.

Novel Blood Biomarkers that Correlate with Cognitive Performance and Hippocampal Volumetry: Potential for Early Diagnosis of Alzheimer's Disease.

BACKGROUND: Differential diagnosis of people presenting with mild cognitive impairment (MCI) that will progress to Alzheimer's disease (AD) remains clinically challenging. Current criteria used to define AD include a series of neuropsychological assessments together with relevant imaging analysis such as magnetic resonance imaging (MRI). The clinical sensitivity and specificity of these assessments would be improved by the concomitant use of novel serum biomarkers. The branched chain aminotransferase proteins (BCAT) are potential candidates as they are significantly elevated in AD brain, correlate with Braak Stage, and may have a role in AD pathology. OBJECTIVE: In this hypothesis-driven project, we aimed to establish if serum BCAT and its metabolites are significantly altered in AD participants and assess their role as markers of disease pathology. METHODS: Serum amino acids were measured using a triple quadrupole mass spectrometer for tandem mass spectroscopy together with BCAT levels using western blot analysis, coupled with neuropsychological assessments and MRI. RESULTS: We present data supporting a substantive mutually correlated system between BCAT and glutamate, neuropsychological tests, and MRI for the diagnosis of AD. These three domains, individually, and in combination, show good utility in discriminating between groups. Our model indicates that BCAT and glutamate accurately distinguish between control and AD participants and in combination with the neuropsychological assessment, MoCA, improved the overall sensitivity to 1.00 and specificity to 0.978. CONCLUSION: These findings indicate that BCAT and glutamate have potential to improve the clinical utility and predictive power of existing methods of AD assessment and hold promise as early indicators of disease pathology.

T2 Relaxometry and Diffusion Tensor Indices of the Hippocampus and Entorhinal Cortex Improve Sensitivity and Specificity of MRI to Detect Amnestic Mild Cognitive Impairment and Alzheimer's Disease Dementia.

BACKGROUND: Quantitative T2 and diffusion MRI indices inform about tissue state and microstructure, both of which may be affected by pathology before tissue atrophy. PURPOSE: To evaluate the capability of both volumetric and quantitative MRI (qMRI) of the hippocampus and entorhinal cortex (EC) for classification of amnestic mild cognitive impairment (aMCI) and Alzheimer's disease dementia (ADD). STUDY TYPE: Retrospective cross-sectional study. POPULATION: Consecutive cohorts of healthy age-matched controls (n = 62), aMCI patients (n = 25), and ADD patients (n = 14). FIELD STRENGTH/SEQUENCE: 3T using T1-weighted imaging, T2-weighted imaging, T2 relaxometry and diffusion tensor imaging (DTI). ASSESSMENT: Montreal Cognitive Assessment and paired associate learning tests for cognitive state. Hippocampal subfield volumes by the automated segmentation of hippocampal subfields system from structural brain images. T2 relaxation time and DTI indices quantified for hippocampal subfields. The fraction of voxels with high T2 values (>20 ms above subfield median) was calculated and regionalized for hippocampus and EC. STATISTICAL TESTS: Support vector machine and receiver operating characteristic analyses from cognitive and MRI data. RESULTS: qMRI classified aMCI and ADD with excellent sensitivity (79.0% and 94.5%, respectively) and specificity (85.6% and 86.1%, respectively), superior to volumes alone (70.0% and 84.5% for respective sensitivities; 82.2 and 91.1 for respective specificities) and similar to cognitive tests (61.7% and 87.5% for respective sensitivities; 88.2% and 90.7% for respective specificities). Regions of high T2 are dispersed throughout each hippocampal subfield in aMCI and ADD with higher concentration than controls, and was most pronounced in the EC. No other individual qMRI marker than EC volume can separate aMCI from ADD, however. DATA CONCLUSION: qMRI markers of hippocampal and entorhinal tissue states are sensitive and specific classifiers of aMCI and ADD. They may serve as markers of a neurodegenerative state preceding volume loss. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:445-455.

Ventral Striatal D2/3 Receptor Availability Is Associated with Impulsive Choice Behavior As Well As Limbic Corticostriatal Connectivity.

Background: Low dopamine D2/3 receptor availability in the nucleus accumbens shell is associated with highly impulsive behavior in rats as measured by premature responses in a cued attentional task. However, it is unclear whether dopamine D2/3 receptor availability in the nucleus accumbens is equally linked to intolerance for delayed rewards, a related form of impulsivity. Methods: We investigated the relationship between D2/3 receptor availability in the nucleus accumbens and impulsivity in a delay-discounting task where animals must choose between immediate, small-magnitude rewards and delayed, larger-magnitude rewards. Corticostriatal D2/3 receptor availability was measured in rats stratified for high and low impulsivity using in vivo [18F]fallypride positron emission tomography and ex vivo [3H]raclopride autoradiography. Resting-state functional connectivity in limbic corticostriatal networks was also assessed using fMRI. Results: Delay-discounting task impulsivity was inversely related to D2/3 receptor availability in the nucleus accumbens core but not the dorsal striatum, with higher D2/3 binding in the nucleus accumbens shell of high-impulsive rats compared with low-impulsive rats. D2/3 receptor availability was associated with stronger connectivity between the cingulate cortex and hippocampus of high- vs low-impulsive rats. Conclusions: We conclude that delay-discounting task impulsivity is associated with low D2/3 receptor binding in the nucleus accumbens core. Thus, two related forms of waiting impulsivity-premature responding and delay intolerance in a delay-of-reward task-implicate an involvement of D2/3 receptor availability in the nucleus accumbens shell and core, respectively. This dissociation may be causal or consequential to enhanced functional connectivity of limbic brain circuitry and hold relevance for attention-deficit/hyperactivity disorder, drug addiction, and other psychiatric disorders.