Subcortical Shape Changes, Hippocampal Atrophy and Cortical Thinning in Future Alzheimer's Disease Patients

Effect of a single nonpharmacological intervention on cognitive functioning in older adults with mild-to-moderate Alzheimer's disease: A meta-analysis of randomized controlled trials

Most studies of nonpharmacological interventions have used a combination of medications in experimental and control groups to improve cognitive functioning or to control symptoms, but the results have been inconsistent with respect to the effects of single nonpharmacological interventions on cognitive functioning in older patients with Alzheimer's disease. The aim of this study was to assess the effect of a single nonpharmacological intervention on cognitive functioning in older adults with mild-to-moderate Alzheimer's disease. We conducted a systematic review and meta-analysis in the first week of January 2024, searching eight electronic databases for articles that reflect on non-pharmacological interventions in Alzheimer's disease published between January 1, 1986, and December 31, 2023. All included articles had to be randomized controlled trials. The primary measure was the change in cognitive function before and after the intervention. Data were extracted by two authors and quality was assessed using the Cochrane Handbook. With the exception of the Montreal Cognitive Assessment (MoCA) scale [MD=2.99, 95% CI (-0.66,6.63)], the differences between the intervention group and the control group were significant for all the remaining scales, namely, the Mini-Mental State Examination (MMSE) [SMD=0.65, 95% CI (0.15,1.15)], Activity of Daily Living Scale (ADL) [MD=-2.30, 95% CI (-3.63,0.97)], Quality of Life in Alzheimer's Disease Scale (QoL-AD) [MD=5.03, 95% CI (2.27,7.78)], Neuropsychiatric Inventory (NPI) [MD=-2.16, 95% CI (-3.86,0.46)], and Alzheimer's Disease Assessment Scale-cognitive score (ADAS-cog) [MD=-5.21, 95% CI (-7.89,2.54)]. Subgroup analysis revealed that the most effective intervention was exercise therapy, followed by repetitive transcranial magnetic stimulation. On the other hand, music therapy was not found to be effective. Current evidence suggests that nonpharmacological interventions can be used to improve cognitive functioning in older adults with mild-to-moderate Alzheimer's disease. This study was registered in PROSPERO (registration number: CRD42024497247).

Association of APOE alleles and polygenic profiles comprising APOE-TOMM40-APOC1 variants with Alzheimer's disease neuroimaging markers

INTRODUCTION

TOMM40 and APOC1 variants can modulate the APOE-ε4-related Alzheimer's disease (AD) risk by up to fourfold. We aim to investigate whether the genetic modulation of ε4-related AD risk is reflected in brain morphology.

METHODS

We tested whether 27 magnetic resonance imaging-derived neuroimaging markers of neurodegeneration (volume and thickness in temporo-limbic regions) are associated with APOE-TOMM40-APOC1 polygenic profiles using the National Alzheimer's Coordinating Center Uniform Data Set linked to the AD Genetic Consortium data.

RESULTS

All brain regions studied using structural phenotypes were smaller in individuals with AD. The ε4 allele was associated with smaller limbic (entorhinal, hippocampus, parahippocampus) brain volume and cortical thickness in AD cases than controls. There were significant differences in the associations for the higher-risk and lower-risk ε4-bearing APOE-TOMM40-APOC1 profiles with temporo-limbic region markers.

DISCUSSION

The APOE-AD heterogeneity may be partly attributed to the modulating role of the TOMM40 and APOC1 genes in the APOE cluster.

HIGHLIGHTS

The ε4 allele is associated with smaller values of neuroimaging markers in AD cases. Larger values of neuroimaging markers may protect against AD in the ε4 carriers. TOMM40 and APOC1 variants differentiate AD risk in the ε4 carriers. The same variants can differentiate the links between ε4 and neuroimaging markers.

Cortical Diffusivity, a Biomarker for Early Neuronal Damage, Is Associated with Amyloid-β Deposition: A Pilot Study

Pathological alterations in Alzheimer's disease (AD) begin several years prior to symptom onset. Cortical mean diffusivity (cMD) may be used as a measure of early grey matter damage in AD as it reflects the breakdown of microstructural barriers preceding volumetric changes and affecting cognitive function. We investigated cMD changes early in the disease trajectory and evaluated the influence of amyloid-β (Aβ) and tau deposition. In this cross-sectional study, we analysed multimodal PET, DTI, and MRI data of 87 participants, and stratified them into Aβ-negative and -positive, cognitively normal, mildly cognitively impaired, and AD patients. cMD was significantly increased in Aβ-positive MCI and AD compared with CN in the frontal, parietal, temporal cortex, hippocampus, and medial temporal lobe. cMD was significantly correlated with cortical thickness only in patients without Aβ deposition but not in Aβ-positive patients. Our results suggest that cMD is an early marker of neuronal damage since it is observed simultaneously with Aβ deposition and is correlated with cortical thickness only in subjects without Aβ deposition. cMD changes may be driven by Aβ but not tau, suggesting that direct Aβ toxicity or associated inflammation causes damage to neurons. cMD may provide information about early microstructural changes before macrostructural changes.

Late-onset temporal lobe epilepsy: insights from brain atrophy and Alzheimer's disease biomarkers

Considering the growing age of the world population, the incidence of epilepsy in older adults is expected to increase significantly. It has been suggested that late-onset temporal lobe epilepsy (LO-TLE) may be neurodegenerative in origin and overlap with Alzheimer's disease (AD). Herein, we aimed to characterize the pattern of cortical atrophy and CSF biomarkers of AD (total and phosphorylated tau and amyloid-β) in a selected population of LO-TLE of unknown origin. We prospectively enrolled individuals with temporal lobe epilepsy onset after the age of 50 and no cognitive impairment. They underwent a structural MRI scan and CSF biomarkers measurement. Imaging and biomarkers data were compared to three retrospectively collected groups: (i) age-sex-matched healthy controls; (ii) patients with mild cognitive impairment (MCI) and abnormal CSF AD biomarkers (MCI-AD); and (iii) patients with MCI and normal CSF AD biomarkers (MCI-noAD). From a pool of 52 patients, 20 consecutive eligible LO-TLE patients with a mean disease duration of 1.8 years were recruited. As control populations, 25 patients with MCI-AD, 25 patients with MCI-noAD and 25 healthy controls were enrolled. CSF biomarkers returned normal values in LO-TLE, significantly different from patients with MCI due to AD. There were no differences in cortico-subcortical atrophy between epilepsy patients and healthy controls, while patients with MCI demonstrated widespread injuries of cortico-subcortical structures. Individuals with LO-TLE, characterized by short disease duration and normal CSF amyloid-β and tau protein levels, showed patterns of cortical thickness and subcortical volumes not significantly different from healthy controls, but highly different from patients with MCI, either due to AD or not.

TOMM40 may mediate GFAP, neurofilament light Protein, pTau181, and brain morphometry in aging

A growing amount of data has implicated the TOMM40 gene in the risk for Alzheimer's disease (AD), neurodegeneration, and accelerated aging. No studies have investigated the relationship of TOMM40 rs2075650 ('650) on the structural complexity of the brain or plasma markers of neurodegeneration. We used a comprehensive approach to quantify the impact of TOMM40 '650 on brain morphology and multiple cortical attributes in cognitively unimpaired (CU) individuals. We also tested whether the presence of the risk allele, G, of TOMM40 '650 was associated with plasma markers of amyloid, tau, and neurodegeneration and if there were interactions with age and sex, controlling for the effects of APOE ε4. We found that the TOMM40 '650 G-allele was associated with decreased sulcal depth, increased gyrification index, and decreased gray matter volume. NfL, GFAP, and pTau181 had independent and age-associated increases in individuals with a G-allele. Our data suggest that TOMM40 '650 is associated with aging-related plasma biomarkers and brain structure variation in temporal-limbic circuits.

Identification and cognitive function prediction of Alzheimer's disease based on multivariate pattern analysis of hippocampal volumes

BACKGROUND

Alzheimer's disease (AD) is strongly associated with slowly progressive hippocampal atrophy. Elucidating the relationships between local morphometric changes and disease status for early diagnosis could be aided by machine learning algorithms trained on neuroimaging datasets.

OBJECTIVE

This study intended to propose machine learning models for the accurate identification and cognitive function prediction across the AD severity spectrum based on structural magnetic resonance imaging (sMRI) of the bilateral hippocampi.

METHODS

The high-resolution sMRI data of 120 AD dementia patients, 232 amnestic mild cognitive impairment (aMCI) patients, and 206 healthy controls (HCs) were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The classification capacity and cognitive predict ability of hippocampal volume was evaluated by multiple pattern analysis using the support vector machine (SVM) and relevance vector regression (RVR) application of the Pattern Recognition for Neuroimaging Toolbox, separately. For validation, the analyses were performed using a biomarker-based regrouping method and another independent local dataset.

RESULTS

The SVM application produced a total accuracy of 94.17%, 80.85%, and 70.74% and area under receiver operating characteristic curves of 0.97, 0.87, and 0.72 between HC versus AD dementia, HC versus aMCI, and aMCI versus AD dementia classification, respectively. The RVR application significantly predicted the baseline and mean cognitive function at three years of follow-up. Qualitatively consistent results were obtained using different regrouping method and the local dataset.

CONCLUSIONS

The machine learning methods based on the bilateral hippocampi distinguished across the AD severity spectrum and predicted the baseline and the longitudinal cognitive function with greater accuracy.

Deep learning techniques for Alzheimer's disease detection in 3D imaging: A systematic review

Background and Aims

Alzheimer's disease (AD) is a degenerative neurological condition that worsens over time and leads to deterioration in cognitive abilities, reduced memory, and, eventually, a decrease in overall functioning. Timely and correct identification of Alzheimer's is essential for effective treatment. The systematic study specifically examines the application of deep learning (DL) algorithms in identifying AD using three-dimensional (3D) imaging methods. The main goal is to evaluate these methods' current state, efficiency, and potential enhancements, offering valuable insights into how DL could improve AD's rapid and precise diagnosis.

Methods

We searched different online repositories, such as IEEE Xplore, Elsevier, MDPI, PubMed Central, Science Direct, ACM, Springer, and others, to thoroughly summarize current research on DL methods to diagnose AD by analyzing 3D imaging data published between 2020 and 2024. We use PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure the organization and understandability of the information collection process. We thoroughly analyzed the literature to determine the primary techniques used in these investigations and their findings.

Results and Conclusion

The ability of convolutional neural networks (CNNs) and their variations, including 3D CNNs and recurrent neural networks, to detect both temporal and spatial characteristics in volumetric data has led to their widespread use. Methods such as transfer learning, combining multimodal data, and using attention procedures have improved models' precision and reliability. We selected 87 articles for evaluation. Out of these, 31 papers included various concepts, explanations, and elucidations of models and theories, while the other 56 papers primarily concentrated on issues related to practical implementation. This article introduces popular imaging types, 3D imaging for Alzheimer's detection, discusses the benefits and restrictions of the DL-based approach to AD assessment, and gives a view toward future developments resulting from critical evaluation.

Loss of glycine receptors in the nucleus accumbens and ethanol reward in an Alzheimer´s Disease mouse model

Alterations in cognitive and non-cognitive cerebral functions characterize Alzheimer's disease (AD). Cortical and hippocampal impairments related to extracellular accumulation of Aβ in AD animal models have been extensively investigated. However, recent reports have also implicated intracellular Aβ in limbic regions, such as the nucleus accumbens (nAc). Accumbal neurons express high levels of inhibitory glycine receptors (GlyRs) that are allosterically modulated by ethanol and have a role in controlling its intake. In the present study, we investigated how GlyRs in the 2xTg mice (AD model) affect nAc functions and ethanol intake behavior. Using transgenic and control aged-matched litter mates, we found that the GlyRα2 subunit was significantly decreased in AD mice (6-month-old). We also examined intracellular calcium dynamics using the fluorescent calcium protein reporter GCaMP in slice photometry. We also found that the calcium signal mediated by GlyRs, but not GABAAR, was also reduced in AD neurons. Additionally, ethanol potentiation was significantly decreased in accumbal neurons in the AD mice. Finally, we performed drinking in the dark (DID) experiments and found that 2xTg mice consumed less ethanol on the last day of DID, in agreement with a lower blood ethanol concentration. 2xTg mice also showed lower sucrose consumption, indicating that overall food reward was altered. In conclusion, the data support the role of GlyRs in nAc neuron excitability and a decreased glycinergic activity in the 2xTg mice that might lead to impairment in reward processing at an early stage of the disease.

Patterns of longitudinal subcortical atrophy over one year in amnestic mild cognitive impairment and its impact on cognitive performance: a preliminary study

Background/aim

Amnestic mild cognitive impairment (aMCI) is a risk factor for dementia, and thus, it is of interest to enlighten specific brain atrophy patterns in aMCI patients. We aim to define the longitudinal atrophy pattern in subcortical structures and its effect on cognition in patients with aMCI.

Materials and methods

Twenty patients with aMCI and 20 demographically matched healthy controls with baseline and longitudinal structural magnetic resonance imaging scans and neuropsychological assessments were studied. The algorithm FIRST (FMRIB's integrated registration and segmentation tool) was used to obtain volumes of subcortical structures (thalamus, putamen, caudate nucleus, nucleus accumbens, globus pallidus, hippocampus, and amygdala). Correlations between volumes and cognitive performance were assessed.

Results

Compared with healthy controls, aMCI demonstrated subcortical atrophies in the hippocampus (p = 0.001), nucleus accumbens (p = 0.003), and thalamus (p = 0.003) at baseline. Significant associations were found for the baseline volumes of the thalamus, nucleus accumbens, and hippocampus with memory, the thalamus with visuospatial skills.

Conclusion

aMCI demonstrated subcortical atrophies associated with cognitive deficits. The thalamus, nucleus accumbens, and hippocampus may provide additional diagnostic information for aMCI.

Relationship between hippocampal subfield volumes and cognitive decline in healthy subjects

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

Piecing it together: atrophy profiles of hippocampal subfields relate to cognitive impairment along the Alzheimer's disease spectrum

Introduction

People with Alzheimer's disease (AD) experience more rapid declines in their ability to form hippocampal-dependent memories than cognitively normal healthy adults. Degeneration of the whole hippocampal formation has previously been found to covary with declines in learning and memory, but the associations between subfield-specific hippocampal neurodegeneration and cognitive impairments are not well characterized in AD. To improve prognostic procedures, it is critical to establish in which hippocampal subfields atrophy relates to domain-specific cognitive declines among people along the AD spectrum. In this study, we examine high-resolution structural magnetic resonance imaging (MRI) of the medial temporal lobe and extensive neuropsychological data from 29 amyloid-positive people on the AD spectrum and 17 demographically-matched amyloid-negative healthy controls.

Methods

Participants completed a battery of neuropsychological exams including select tests of immediate recollection, delayed recollection, and general cognitive status (i.e., performance on the Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]). Hippocampal subfield volumes (CA1, CA2, CA3, dentate gyrus, and subiculum) were measured using a dedicated MRI slab sequence targeting the medial temporal lobe and used to compute distance metrics to quantify AD spectrum-specific atrophic patterns and their impact on cognitive outcomes.

Results

Our results replicate prior studies showing that CA1, dentate gyrus, and subiculum hippocampal subfield volumes were significantly reduced in AD spectrum participants compared to amyloid-negative controls, whereas CA2 and CA3 did not exhibit such patterns of atrophy. Moreover, degeneration of the subiculum along the AD spectrum was linked to a significant decline in general cognitive status measured by the MMSE, while degeneration scores of the CA1 and dentate gyrus were more widely associated with declines on the MMSE and tests of learning and memory.

Discussion

These findings provide evidence that subfield-specific patterns of hippocampal degeneration, in combination with cognitive assessments, may constitute a sensitive prognostic approach and could be used to better track disease trajectories among individuals on the AD spectrum.

Bone Marrow-Derived Mesenchymal Stem Cells and γ-Secretase Inhibitor Treatments Suppress Amyloid-β25-35-Induced Cognitive Impairment in Rat Dams and Cortical Degeneration in Offspring

Alzheimer's disease (AD) is the most frequent cause of age-related neurodegeneration and ensuing cognitive impairment. Progressive deposition of extracellular amyloid beta (Aβ) aggregates (plaques) and intracellular hyperphosphorylated Tau protein (p-Tau) are the core pathological markers of AD but may precede clinical symptoms by many years, presenting a therapeutic window of opportunity. Females are more frequently afflicted by AD than males, necessitating evaluation of novel treatments for the female population. The current study examined the protective efficacies of intravenous bone marrow-derived mesenchymal stem cells (BM-MSCs) and oral gamma-secretase inhibitor-953 (GSI-953) during pregnancy on cognitive impairment in rat dams and neurodegeneration in offspring induced by intracerebroventricular injection of Aβ25-35 prior to pregnancy. The Aβ25-35 (AD) group exhibited significant (P < 0.001) impairments in the Y-maze and novel object recognition test performance prior to conception. Histological analysis of the offspring cortex revealed substantial dendritic shrinkage and activation of microglial cells, while neurochemical analysis demonstrated significant increases in the proinflammatory cytokine interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α). In contrast, BM-MSC or GSI-953 treatment of dams following Aβ25-35 injection significantly (P < 0.001) reduced the number and size of activated microglial cells, markedly increased dendrite length, and reversed proinflammatory cytokine elevations in offspring. Moreover, BM-MSC or GSI-953 treatment reversed the Aβ25-35-induced amyloid precursor protein and p-Tau elevations in the offspring brain; these changes were accompanied by upregulation of the brain-derived neurotrophic factor and downregulation of glycogen synthase kinase-3β in the serum and brain. Treatment with BM-MSCs or GSI-953 also reversed Aβ25-35-induced elevations in different gene expressions in the neonatal cortex. Finally, treatment of dams with BM-MSCs or GSI-953 prevented the Aβ25-35-induced disruption of newborn brain development. Thus, BM-MSC and GSI-953 treatments have broad-spectrum effects against Aβ25-35-induced brain pathology, including the suppression of neural inflammation, restoration of developmental plasticity, and promotion of neurotrophic signaling.

Secondary thalamic atrophy related to brain infarction may contribute to post-stroke cognitive impairment

BACKGROUND AND PURPOSE

The thalamus is a key brain hub that is globally connected to many cortical regions. Previous work highlights thalamic contributions to multiple cognitive functions, but few studies have measured thalamic volume changes or cognitive correlates. This study investigates associations between thalamic volumes and post-stroke cognitive function.

METHODS

Participants with non-thalamic brain infarcts (3-42 months) underwent MRI and cognitive testing. Focal infarcts and thalami were traced manually. In cases with bilateral infarcts, the side of the primary infarct volume defined the hemisphere involved. Brain parcellation and volumetrics were extracted using a standardized and previously validated neuroimaging pipeline. Age and gender-matched healthy controls provided normal comparative thalamic volumes. Thalamic atrophy was considered when the volume exceeded 2 standard deviations greater than the controls.

RESULTS

Thalamic volumes ipsilateral to the infarct in stroke patients (n=55) were smaller than left (4.4 ± 1.4 vs. 5.4 ± 0.5 cc, p < 0.001) and right (4.4 ± 1.4 vs. 5.5 ± 0.6 cc, p < 0.001) thalamic volumes in the controls. After controlling for head-size and global brain atrophy, infarct volume independently correlated with ipsilateral thalamic volume (β= -0.069, p=0.024). Left thalamic atrophy correlated significantly with poorer cognitive performance (β = 4.177, p = 0.008), after controlling for demographics and infarct volumes.

CONCLUSIONS

Our results suggest that the remote effect of infarction on ipsilateral thalamic volume is associated with global post-stroke cognitive impairment.

Microstructural mapping of dentate gyrus pathology in Alzheimer's disease: A 16.4 Tesla MRI study

The dentate gyrus (DG) is an integral portion of the hippocampal formation, and it is composed of three layers. Quantitative magnetic resonance (MR) imaging has the capability to map brain tissue microstructural properties which can be exploited to investigate neurodegeneration in Alzheimer's disease (AD). However, assessing subtle pathological changes within layers requires high resolution imaging and histological validation. In this study, we utilized a 16.4 Tesla scanner to acquire ex vivo multi-parameter quantitative MRI measures in human specimens across the layers of the DG. Using quantitative diffusion tensor imaging (DTI) and multi-parameter MR measurements acquired from AD (N = 4) and cognitively normal control (N = 6) tissues, we performed correlation analyses with histological measurements. Here, we found that quantitative MRI measures were significantly correlated with neurofilament and phosphorylated Tau density, suggesting sensitivity to layer-specific changes in the DG of AD tissues.

Associations of cortical iron accumulation with cognition and cerebral atrophy in Alzheimer's disease

BACKGROUND

In Alzheimer's disease (AD), cerebral iron accumulation colocalizes with the pathological proteins amyloid-β (Aβ) and tau. Furthermore, tau-induced cortical thinning is associated with cognitive decline. In this study, quantitative susceptibility mapping (QSM) was used to investigate the whole-brain distribution pattern of cortical iron deposition and its relationships with cognition and cortical thickness in AD.

METHODS

This cross-sectional study prospectively recruited 30 participants with AD and 26 age- and sex-matched healthy controls (HCs). All participants underwent QSM and T1-weighted examinations on a 3.0T MRI scanner. Global cognition was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Whole-brain cross-sectional QSM analysis and whole-brain QSM regression analyses against the MMSE and MoCA scores were performed. Surface-based morphometry analysis was also performed. Subsequently, in regions with significant atrophy, magnetic susceptibility was compared between the AD and HC groups, and the association between magnetic susceptibility and cortical thickness was assessed.

RESULTS

Whole-brain QSM cross-sectional analysis in the AD group demonstrated widespread increased susceptibility across the cortical ribbon, asymmetrically covering the left hemisphere cerebral cortex, caudate nucleus, putamen, and partial cerebellar cortex. Whole-brain QSM regression analyses in the AD group showed that increased susceptibility covaried with lower MMSE and MoCA scores, and was predominantly located in the right parietal cortex and lateral occipital cortex. In the AD group, cortical thickness was reduced in the left superior temporal gyrus, right frontal pole, fusiform gyus, and pars opercularis, and there were increases in susceptibility in the right frontal pole (AD: mean ± SD 0.034±0.007 ppm, 95% CI: 0.032-0.037 ppm; HC: 0.030±0.005 ppm, 95% CI: 0.028-0.032 ppm; P=0.016) and pars opercularis (AD: 0.020±0.003 ppm, 95% CI: 0.018-0.021 ppm; HC: 0.017±0.002 ppm, 95% CI: 0.017-0.018 ppm; P=0.002). Susceptibility was negatively correlated with cortical thickness in the right pars opercularis in the entire cohort (r=-0.521, P<0.001) and AD group (r=-0.510, P=0.005).

CONCLUSIONS

Widespread cortical iron, as measured by QSM, accumulated in AD and iron deposition was associated with poor cognitive performance. Increased iron content was also associated with brain atrophy. Our study suggests QSM may be a useful imaging biomarker for monitoring the neurodegenerative progression of AD.

Neuroimaging Markers for Determining Former American Football Players at Risk for Alzheimer's Disease

NFL players, by virtue of their exposure to traumatic brain injury (TBI), are at higher risk of developing dementia and Alzheimer's disease (AD) than the general population. Early recognition and intervention before the onset of clinical symptoms could potentially avert/delay the long-term consequences of these diseases. Given that AD is thought to have a long pre-clinical incubation period, the aim of the current research was to determine whether former NFL players show evidence of incipient dementia in their structural imaging before diagnosis of AD. To identify neuroimaging markers of AD, against which former NFL players would be compared, we conducted a whole-brain volumetric analysis using a cohort of AD patients (ADNI clinical database) to produce a set of brain regions demonstrating sensitivity to early AD pathology (i.e., the “AD fingerprint”). A group of 46 former NFL players' brain magnetic resonance images were then interrogated using the AD fingerprint, that is, the former NFL subjects were compared volumetrically to AD patients using a T1-weighted magnetization-prepared rapid gradient echo sequence. The FreeSurfer image analysis suite (version 6.0) was used to obtain volumetric and cortical thickness data. The Automated Neuropsychological Assessment Metric-Version 4 was used to assess current cognitive functioning. A total of 55 brain regions demonstrated significant atrophy or ex vacuo dilatation bilaterally in AD patients versus controls. Of the 46 former NFL players, 41% demonstrated a greater than expected number of atrophied/dilated AD regions compared with age-matched controls, presumably reflecting AD pathology.

Fractal dimension of the brain in neurodegenerative disease and dementia: A systematic review

Sensitive and specific antemortem biomarkers of neurodegenerative disease and dementia are crucial to the pursuit of effective treatments, required both to reliably identify disease and to track its progression. Atrophy is the structural magnetic resonance imaging (MRI) hallmark of neurodegeneration. However in most cases it likely indicates a relatively advanced stage of disease less susceptible to treatment as some disease processes begin decades prior to clinical onset. Among emerging metrics that characterise brain shape rather than volume, fractal dimension (FD) quantifies shape complexity. FD has been applied in diverse fields of science to measure subtle changes in elaborate structures. We review its application thus far to structural MRI of the brain in neurodegenerative disease and dementia. We identified studies involving subjects who met criteria for mild cognitive impairment, Alzheimer's Disease, Vascular Dementia, Lewy Body Dementia, Frontotemporal Dementia, Amyotrophic Lateral Sclerosis, Parkinson's Disease, Huntington's Disease, Multiple Systems Atrophy, Spinocerebellar Ataxia and Multiple Sclerosis. The early literature suggests that neurodegenerative disease processes are usually associated with a decline in FD of the brain. The literature includes examples of disease-related change in FD occurring independently of atrophy, which if substantiated would represent a valuable advantage over other structural imaging metrics. However, it is likely to be non-specific and to exhibit complex spatial and temporal patterns. A more harmonious methodological approach across a larger number of studies as well as careful attention to technical factors associated with image processing and FD measurement will help to better elucidate the metric's utility.

Subcortical and Cerebellar Neural Correlates of Prodromal Alzheimer’s Disease with Prolonged Sleep Latency

Background: Despite the important associations among sleep, Alzheimer’s disease (AD), subcortical structures, and the cerebellum, structural and functional magnetic resonance imaging (MRI) with regard to these regions and sleep on patients in AD trajectory are scarce. Objective: This study aimed to evaluate the influence of prolonged sleep latency on the structural and functional alterations in the subcortical and cerebellar neural correlates in amyloid-β positive amnestic mild cognitive impairment patients (Aβ+aMCI). Methods: A total of 60 patients with aMCI who were identified as amyloid positive ([18F] flutemetamol+) were recruited in the study, 24 patients with normal sleep latency (aMCI-n) and 36 patients prolonged sleep latency (aMCI-p). Cortical thickness and volumes between the two groups were compared. Volumetric analyses were implemented on the brainstem, thalamus, and hippocampus. Subcortical and cerebellar resting state functional connectivity (FC) differences were measured between the both groups through seed-to-voxel analysis. Additionally, group x Aβ interactive effects on FC values were tested with a general linear model. Result: There was a significantly decreased brainstem volume in aMCI-p subjects. We observed a significant reduction of the locus coeruleus (LC) FC with frontal, temporal, insular cortices, hippocampus, and left thalamic FC with occipital cortex. Moreover, the LC FC with occipital cortex and left hippocampal FC with frontal cortex were increased in aMCI-p subjects. In addition, there was a statistically significant group by regional standardized uptake value ratio interactions discovered in cerebro-cerebellar networks. Conclusion: The aforementioned findings suggest that prolonged sleep latency may be a detrimental factor in compromising structural and functional correlates of subcortical structures and the cerebellum, which may accelerate AD pathophysiology.

Histological and imunohistochemical alterations of hippocampus and prefrontal cortex in a rat model of Alzheimer like-disease with a preferential role of the flavonoid "hesperidin"

Alzheimer's disease (AD) is a chronic age-related neurodegenerative disease characterized by degeneration of the central cholinergic neurons, inflammation and oxidative stress in the basal forebrain, prefrontal cortex and hippocampus. Hesperidin (Hesp) is one of the flavonoids havinganti-inflammatory and anti-oxidative properties in some neurodegerative brain lesions. To investigate the possible neuroprotective role of Hespin an AD-like rat model induced experimentally by Scopolamine (Scop). Forty adult male Sprague Dawley rats were randomly allocated into four groups. Group I-(Control), group II-(Hesp) (supplemented orally with 100 mg/kg Hesp for 28 days), group III-(AD) (injected i.p with 1 mg/kg Scop for 9 days) and group IV-(Hesp/AD). At the end of the experiment, behavioral (Y-maze test) and biochemical analysis were carried out along with histological, immunohistochemical and morphometric studies of the hippocampus and prefrontal cortex. AD rats displayed memory impairment in the behavioural paradigm with a concomitant increase of serum TNF-α and IL-1β, while IL-10 decreased significantly. Also, there was a rise of amyloid beta-42 (Aβ-42), acetylcholinesterase (AChE) activity and malondialdehyde (MDA) together with a decrease of reduced glutathione (GSH) in hippocampal and prefrontal homogenate. In addition, sections of the hippocampus and prefrontal cortex revealed obvious histopathological changes, overexpression of p-Tau protein and glial fibrillary acidic protein (GFAP) with a decrease in the expression of synaptophysin (SYN). Contradictorily, pre-treatment with Hesp offset the spatial memory deficits, redox imbalance, Aβ-42 and AChE over activity as well as preserved the histological architecture and attenuated the raised p-Tau protein and GFAP while upregulated SYN immuoreactivity of AD rats. Collectively, our results highlight the potential mitigating role of Hesp in AD-like state in rats and this may presumably raise the possibility of its future implementation as a prophylactic remedy against AD in humans.

Pain relief reverses hippocampal abnormalities in trigeminal neuralgia

Chronic pain patients frequently report memory and concentration difficulties. Objective testing in this population points to poor performance on memory and cognitive tests, and increased comorbid anxiety and depression. Recent evidence has suggested convergence between chronic pain and memory deficits onto the hippocampus. The hippocampus consists of heterogenous subfields involved in memory consolidation, behavior regulation, and stress modulation. Despite significant studies outlining hippocampal changes in human and chronic pain animal models, the effect of pain relief on hippocampal abnormalities remains unknown. Trigeminal neuralgia (TN) is a chronic neuropathic pain disorder which is highly amenable to surgical interventions, providing a unique opportunity to investigate the effect of pain relief. This study investigates the effect of pain relief on hippocampal subfields in TN. Anatomical MR images of 61 TN patients were examined before and 6 months after surgery. Treatment responders (n=47) reported 95% pain relief, whereas non-responders (n=14) reported 40% change in pain on average. At baseline, patients had smaller hippocampal volumes, compared to controls. After surgery, responders' hippocampal volumes normalized, largely driven by CA2/3, CA4 and dentate gyrus, which are involved in memory consolidation and neurogenesis. We propose that hippocampal atrophy in TN is pain-driven and successful treatment normalizes such abnormalities.

Enhanced detection of cortical atrophy in Alzheimer's disease using structural MRI with anatomically constrained longitudinal registration

Cortical atrophy is a defining feature of Alzheimer's disease (AD), often detectable before symptoms arise. In surface-based analyses, studies have commonly focused on cortical thinning while overlooking the impact of loss in surface area. To capture the impact of both cortical thinning and surface area loss, we used anatomically constrained Multimodal Surface Matching (aMSM), a recently developed tool for mapping change in surface area. We examined cortical atrophy over 2 years in cognitively normal subjects and subjects with diagnoses of stable mild cognitive impairment, mild cognitive impairment that converted to AD, and AD. Magnetic resonance imaging scans were segmented and registered to a common atlas using previously described techniques (FreeSurfer and ciftify), then longitudinally registered with aMSM. Changes in cortical thickness, surface area, and volume were mapped within each diagnostic group, and groups were compared statistically. Changes in thickness and surface area detected atrophy at similar levels of significance, though regions of atrophy somewhat differed. Furthermore, we found that surface area maps offered greater consistency across scanners (3.0 vs. 1.5 T). Comparisons to the FreeSurfer longitudinal pipeline and parcellation-based (region-of-interest) analysis suggest that aMSM may allow more robust detection of atrophy, particularly in earlier disease stages and using smaller sample sizes.

Association between structural brain features and gene expression by weighted gene co-expression network analysis in conversion from MCI to AD

Alzheimer's disease (AD) is a neurodegenerative disease. Mild cognitive impairment (MCI) represents a state of cognitive function between normal cognition and dementia. Longitudinal studies showed that some MCI patients remained in a state of MCI, and some developed AD. The reason for these different conversions from MCI remains to be investigated. 180 MCI participants were followed for eight years. 143 MCI patients maintained the MCI state (MCI_S), and the remaining thirty-seven MCI patients were re-evaluated as having AD (MCI_AD). We obtained 1,036 structural brain characteristics and 15,481 gene expression values from the 180 MCI participants and applied weighted gene co-expression network analysis (WGCNA) to explore the relationship between structural brain features and gene expression. Regulating mediator effect analysis was employed to explore the relationships among gene expression, brain region measurements and clinical phenotypes. We found that 60 genes from the MCI_S group and 18 genes from the MCI_AD group respectively had the most significant correlations with left paracentral lobule and sulcus (L.PTS) and right subparietal sulcus (R.SubPS) thickness; CTCF, UQCR11 and WDR5B were the mutual genes between the two groups. The expression of CTCF gene and clinical score are completely mediated by L.PTS thickness, and the UQCR11 and WDR5B gene expression levels significantly regulate the mediating effect pathway. In conclusion, the factors affecting the different conversions from MCI are closely related to L.PTS thickness and the CTCF, UQCR11 and WDR5B gene expression levels. Our results add a theoretical foundation of imaging genetics for conversion from MCI to AD.

FreeSurfer ‐based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized.

Changes in neuronal excitability and synaptic transmission in nucleus accumbens in a transgenic Alzheimer's disease mouse model

Several previous studies showed that hippocampus and cortex are affected in Alzheimer's disease (AD). However, other brain regions have also been found to be affected and could contribute with new critical information to the pathophysiological basis of AD. For example, volumetric studies in humans have shown a significant atrophy of the striatum, particularly in the nucleus Accumbens (nAc). The nAc is a key component of the limbic reward system and it is involved in cognition and emotional behaviors such as pleasure, fear, aggression and motivations, all of which are affected in neurodegenerative diseases such as AD. However, its role in AD has not been extensively studied. Therefore, using an AD mouse model, we investigated if the nAc was affected in 6 months old transgenic 2xTg (APP/PS1) mice. Immunohistochemistry (IHC) analysis in 2xTg mice showed increased intraneuronal Aβ accumulation, as well as occasional extracellular amyloid deposits detected through Thioflavin-S staining. Interestingly, the intracellular Aβ pathology was associated to an increase in membrane excitability in dissociated medium spiny neurons (MSNs) of the nAc. IHC and western blot analyses showed a decrease in glycine receptors (GlyR) together with a reduction in the pre- and post-synaptic markers SV2 and gephyrin, respectively, which correlated with a decrease in glycinergic miniature synaptic currents in nAc brain slices. Additionally, voltage-clamp recordings in dissociated MSNs showed a decrease in AMPA- and Gly-evoked currents. Overall, these results showed intracellular Aβ accumulation together with an increase in excitability and synaptic alterations in this mouse model. These findings provide new information that might help to explain changes in motivation, anhedonia, and learning in the onset of AD pathogenesis.

Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

We propose a mesh-based technique to aid in the classification of Alzheimer's disease dementia (ADD) using mesh representations of the cortex and subcortical structures. Deep learning methods for classification tasks that utilize structural neuroimaging often require extensive learning parameters to optimize. Frequently, these approaches for automated medical diagnosis also lack visual interpretability for areas in the brain involved in making a diagnosis. This work: (a) analyzes brain shape using surface information of the cortex and subcortical structures, (b) proposes a residual learning framework for state-of-the-art graph convolutional networks which offer a significant reduction in learnable parameters, and (c) offers visual interpretability of the network via class-specific gradient information that localizes important regions of interest in our inputs. With our proposed method leveraging the use of cortical and subcortical surface information, we outperform other machine learning methods with a 96.35% testing accuracy for the ADD vs. healthy control problem. We confirm the validity of our model by observing its performance in a 25-trial Monte Carlo cross-validation. The generated visualization maps in our study show correspondences with current knowledge regarding the structural localization of pathological changes in the brain associated to dementia of the Alzheimer's type.

Characterizing the Subcortical Structures in Youth with Congenital Heart Disease

BACKGROUND AND PURPOSE

Congenital heart disease is a leading cause of neurocognitive impairment. Many subcortical structures are known to play a crucial role in higher-order cognitive processing. However, comprehensive anatomic characterization of these structures is currently lacking in the congenital heart disease population. Therefore, this study aimed to compare the morphometry and volume of the globus pallidus, striatum, and thalamus between youth born with congenital heart disease and healthy peers.

MATERIALS AND METHODS

We recruited youth between 16 and 24 years of age born with congenital heart disease who underwent cardiopulmonary bypass surgery before 2 years of age (n = 48) and healthy controls of the same age (n = 48). All participants underwent a brain MR imaging to acquire high-resolution 3D T1-weighted images.

RESULTS

Smaller surface area and inward bilateral displacement across the lateral surfaces of the globus pallidus were concentrated anteriorly in the congenital heart disease group compared with controls (q < 0.15). On the lateral surfaces of bilateral thalami, we found regions of both larger and smaller surface areas, as well as inward and outward displacement in the congenital heart disease group compared with controls (q < 0.15). We did not find any morphometric differences between groups for the striatum. For the volumetric analyses, only the right globus pallidus showed a significant volume reduction (q < 0.05) in the congenital heart disease group compared with controls.

CONCLUSIONS

This study reports morphometric alterations in youth with congenital heart disease in the absence of volume reductions, suggesting that volume alone is not sufficient to detect and explain subtle neuroanatomic differences in this clinical population.

Imaging biomarkers in neurodegeneration: current and future practices

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course "Biomarkers in neurodegenerative diseases". In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

Differentiation Drives Widespread Rewiring of the Neural Stem Cell Chaperone Network

Neural stem and progenitor cells (NSPCs) are critical for continued cellular replacement in the adult brain. Lifelong maintenance of a functional NSPC pool necessitates stringent mechanisms to preserve a pristine proteome. We find that the NSPC chaperone network robustly maintains misfolded protein solubility and stress resilience through high levels of the ATP-dependent chaperonin TRiC/CCT. Strikingly, NSPC differentiation rewires the cellular chaperone network, reducing TRiC/CCT levels and inducing those of the ATP-independent small heat shock proteins (sHSPs). This switches the proteostasis strategy in neural progeny cells to promote sequestration of misfolded proteins into protective inclusions. The chaperone network of NSPCs is more effective than that of differentiated cells, leading to improved management of proteotoxic stress and amyloidogenic proteins. However, NSPC proteostasis is impaired by brain aging. The less efficient chaperone network of differentiated neural progeny may contribute to their enhanced susceptibility to neurodegenerative diseases characterized by aberrant protein misfolding and aggregation.

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year.

OBJECTIVES

To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI.

SEARCH METHODS

On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches.

SELECTION CRITERIA

We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter.

DATA COLLECTION AND ANALYSIS

Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available.

MAIN RESULTS

We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate.

AUTHORS' CONCLUSIONS

The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.

Interactive effects of age and recent substance use on striatal shape morphology at substance use disorder treatment entry

BACKGROUND

Striatal neuroadaptations are regarded to play an important role in the progression from voluntary to compulsive use of addictive substances and provide a promising target for the identification of neuroimaging biomarkers. Recent advances in surface-based computational analysis enable morphological assessment linking variations in global and local striatal shape to duration and magnitude of substance use with a degree of sensitivity that exceeds standard volumetric analysis.

METHODS

This study used a new segmentation methodology coupled with local surface-based indices of surface area and displacement to provide a comprehensive structural characterization of the striatum in 34 patients entering treatment for substance use disorder (SUD) and 49 controls, and to examine the influence of recent substance use on abnormal age-related striatal deformation in SUD patients.

RESULTS

Patients showed a small reduction in striatal volume and no difference in surface area or shape in comparison to controls. Between-group differences in shape were likely neutralized by the bidirectional influence of recent substance use on striatal shape in SUD patients. Specifically, there was an interaction between age and substance such that among older patients more drug use was associated with greater inward striatal contraction but more alcohol use was associated with greater outward expansion.

CONCLUSIONS

This study builds on previous work and advances our understanding of the nature of striatal neuroadaptations as a potential biomarker of disease progression in addiction.

Pathways of Prevention: A Scoping Review of Dietary and Exercise Interventions for Neurocognition

Alzheimer's disease and related dementias (ADRD) represent an increasingly urgent public health concern, with an increasing number of baby boomers now at risk. Due to a lack of efficacious therapies among symptomatic older adults, an increasing emphasis has been placed on preventive measures that can curb or even prevent ADRD development among middle-aged adults. Lifestyle modification using aerobic exercise and dietary modification represents one of the primary treatment modalities used to mitigate ADRD risk, with an increasing number of trials demonstrating that exercise and dietary change, individually and together, improve neurocognitive performance among middle-aged and older adults. Despite several optimistic findings, examination of treatment changes across lifestyle interventions reveals a variable pattern of improvements, with large individual differences across trials. The present review attempts to synthesize available literature linking lifestyle modification to neurocognitive changes, outline putative mechanisms of treatment improvement, and discuss discrepant trial findings. In addition, previous mechanistic assumptions linking lifestyle to neurocognition are discussed, with a focus on potential solutions to improve our understanding of individual neurocognitive differences in response to lifestyle modification. Specific recommendations include integration of contemporary causal inference approaches for analyzing parallel mechanistic pathways and treatment-exposure interactions. Methodological recommendations include trial multiphase optimization strategy (MOST) design approaches that leverage individual differences for improved treatment outcomes.

Early diagnosis of Alzheimer's disease using combined features from voxel-based morphometry and cortical, subcortical, and hippocampus regions of MRI T1 brain images

In recent years, several high-dimensional, accurate, and effective classification methods have been proposed for the automatic discrimination of the subject between Alzheimer's disease (AD) or its prodromal phase {i.e., mild cognitive impairment (MCI)} and healthy control (HC) persons based on T1-weighted structural magnetic resonance imaging (sMRI). These methods emphasis only on using the individual feature from sMRI images for the classification of AD, MCI, and HC subjects and their achieved classification accuracy is low. However, latest multimodal studies have shown that combining multiple features from different sMRI analysis techniques can improve the classification accuracy for these types of subjects. In this paper, we propose a novel classification technique that precisely distinguishes individuals with AD, aAD (stable MCI, who had not converted to AD within a 36-month time period), and mAD (MCI caused by AD, who had converted to AD within a 36-month time period) from HC individuals. The proposed method combines three different features extracted from structural MR (sMR) images using voxel-based morphometry (VBM), hippocampal volume (HV), and cortical and subcortical segmented region techniques. Three classification experiments were performed (AD vs. HC, aAD vs. mAD, and HC vs. mAD) with 326 subjects (171 elderly controls and 81 AD, 35 aAD, and 39 mAD patients). For the development and validation of the proposed classification method, we acquired the sMR images from the dataset of the National Research Center for Dementia (NRCD). A five-fold cross-validation technique was applied to find the optimal hyperparameters for the classifier, and the classification performance was compared by using three well-known classifiers: K-nearest neighbor, support vector machine, and random forest. Overall, the proposed model with the SVM classifier achieved the best performance on the NRCD dataset. For the individual feature, the VBM technique provided the best results followed by the HV technique. However, the use of combined features improved the classification accuracy and predictive power for the early classification of AD compared to the use of individual features. The most stable and reliable classification results were achieved when combining all extracted features. Additionally, to analyze the efficiency of the proposed model, we used the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to compare the classification performance of the proposed model with those of several state-of-the-art methods.

Subcortical amyloid load is associated with shape and volume in cognitively normal individuals

Amyloid-beta (Aβ) deposition is one of the main hallmarks of Alzheimer's disease. The study assessed the associations between cortical and subcortical ¹¹ C-Pittsburgh Compound B (PiB) retention, namely, in the hippocampus, amygdala, putamen, caudate, pallidum, and thalamus, and subcortical morphology in cognitively normal individuals. We recruited 104 cognitive normal individuals who underwent extensive neuropsychological assessment, PiB-positron emission tomography (PET) scan, and 3-T magnetic resonance imaging (MRI) acquisition of T1-weighted images. Global, cortical, and subcortical regional PiB retention values were derived from each scan and subcortical morphology analyses were performed to investigate vertex-wise local surface and global volumes, including the hippocampal subfields volumes. We found that subcortical regional Aβ was associated with the surface of the hippocampus, thalamus, and pallidum, with changes being due to volume and shape. Hippocampal Aβ was marginally associated with volume of the whole hippocampus as well as with the CA1 subfield, subiculum, and molecular layer. Participants showing higher subcortical Aβ also showed worse cognitive performance and smaller hippocampal volumes. In contrast, global and cortical PiB uptake did not associate with any subcortical metrics. This study shows that subcortical Aβ is associated with subcortical surface morphology in cognitively normal individuals. This study highlights the importance of quantifying subcortical regional PiB retention values in these individuals.

The Medial Septum Is Insulin Resistant in the AD Presymptomatic Phase: Rescue by Nerve Growth Factor-Driven IRS1 Activation

Basal forebrain cholinergic neurons (BFCN) are key modulators of learning and memory and are high energy-demanding neurons. Impaired neuronal metabolism and reduced insulin signaling, known as insulin resistance, has been reported in the early phase of Alzheimer's disease (AD), which has been suggested to be "Type 3 Diabetes." We hypothesized that BFCN may develop insulin resistance and their consequent failure represents one of the earliest event in AD. We found that a condition reminiscent of insulin resistance occurs in the medial septum of 3 months old 3×Tg-AD mice, reported to develop typical AD histopathology and cognitive deficits in adulthood. Further, we obtained insulin resistant BFCN by culturing them with high insulin concentrations. By means of these paradigms, we observed that nerve growth factor (NGF) reduces insulin resistance in vitro and in vivo. NGF activates the insulin receptor substrate 1 (IRS1) and rescues c-Fos expression and glucose metabolism. This effect involves binding of activated IRS1 to the NGF receptor TrkA, and is lost in presence of the specific IRS inhibitor NT157. Overall, our findings indicate that, in a well-established animal model of AD, the medial septum develops insulin resistance several months before it is detectable in the neocortex and hippocampus. Remarkably, NGF counteracts molecular alterations downstream of insulin-resistant receptor and its nasal administration restores insulin signaling in 3×Tg-AD mice by TrkA/IRS1 activation. The cross-talk between NGF and insulin pathways downstream the insulin receptor suggests novel potential therapeutic targets to slow cognitive decline in AD and diabetes-related brain insulin resistance.

The Volume of Hippocampal Subfields in Relation to Decline of Memory Recall Across the Adult Lifespan

Background: The hippocampus is an important limbic structure closely related to memory function. However, few studies have focused on the association between hippocampal subfields and age-related memory decline. We investigated the volume alterations of hippocampal subfields at different ages and assessed the correlations with Immediate and Delayed recall abilities. Materials and Methods: A total of 275 participants aged 20-89 years were classified into 4 groups: Young, 20-35 years; Middle-early, 36-50 years; Middle-late, 51-65 years; Old, 66-89 years. All data were acquired from the Dallas Lifespan Brain Study (DLBS). The volumes of hippocampal subfields were obtained using Freesurfer software. Analysis of covariance (ANCOVA) was performed to analyze alterations of subfield volumes among the 4 groups, and multiple comparisons between groups were performed using the Bonferroni method. Spearman correlation with false discovery rate correction was used to investigate the relationship between memory recall scores and hippocampal subfield volumes. Results: Apart from no significant difference in the left parasubiculum (P = 0.269) and a slight difference in the right parasubiculum (P = 0.022), the volumes of other hippocampal subfields were significantly different across the adult lifespan (P < 0.001). The hippocampal fissure volume was increased in the Old group, while volumes for other subfields decreased. In addition, Immediate recall scores were associated with volumes of the bilateral molecular layer, granule cell layer of the dentate gyrus (GC-DG), cornus ammonis (CA) 1, CA2/3, CA4, left fimbria and hippocampal amygdala transition area (HATA), and right fissure (P < 0.05). Delayed recall scores were associated with the bilateral molecular layer, GC-DG, CA2/3 and CA4; left tail, presubiculum, CA1, subiculum, fimbria and HATA (P < 0.05). Conclusion: The parasubiculum volume was not significantly different across the adult lifespan, while atrophy in dementia patients in some studies. Based on these findings, we speculate that volume changes in this region might be considered as a biomarker for dementia disorders. Additionally, several hippocampal subfield volumes were significantly associated with memory scores, further highlighting the key role of the hippocampus in age-related memory decline. These regions could be used to assess the risk of memory decline across the adult lifespan.

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer's disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, 'shape connections' between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus.