Regional Cortical Thickness Research Articles

Clinically detectable structural abnormalities in pediatric‐onset multiple sclerosis: A large‐scale magnetic resonance imaging analysis

AbstractBackgroundMultiple Sclerosis is characterized by neural demyelination. Structural magnetic resonance imaging (MRI) provides soft tissue contrast, which forms the basis of techniques for extracting regional biomarkers across a participant's brain.ObjectivesTo investigate the clinical presentation of multiple sclerosis in a large‐scale MRI analysis that includes thorough consideration of extractable structural measurements (average and variability of regional cortical thicknesses, cortical surface measurements, and volumes).MethodsWe performed a large‐scale retrospective analysis of 370 T1 structural volumetric MRIs from 64 participants with multiple sclerosis and compared them with a large cohort of neurotypical participants, consisting of 993 MRIs from 988 participants. Regionally distributed measurements of cortical thickness (average and standard deviation) were extracted along with surface area, surface curvature, and volumetric measurements.ResultsThe largest observed finding involved regionally distributed reductions in average cortical thickness, with the parahippocampal region exhibiting the largest effect size, a finding that may be linked with known hippocampal atrophy in multiple sclerosis. Group‐wise differences were also observed in terms of distributed volume, surface area, and surface curvature measurements.ConclusionsParticipants with pediatric‐onset multiple sclerosis present clinically with a variety of structural abnormalities, including perirhinal cortex thickness abnormalities not previously reported in the literature.

Altered structural connectivity networks in dementia with lewy bodies

The impairment of large-scale brain networks has been observed in dementia with Lewy bodies (DLB) using functional connectivity, but the potential for an analogous effect on structural covariance patterns has not been determined. Twenty-four probable DLB subjects (mean age 74.3 ± 6.7 years, 16.7% female) and 23 similarly aged Controls were included. All participants underwent 3T MRI imaging with high-resolution T1-weighted magnetization-prepared rapid gradient echo (MPRAGE) sequence. Graph theoretical analyses were performed using variation in regional cortical thickness to construct a structural association matrix with pairwise Pearson correlations. Global and nodal graph parameters were computed to assess between-group differences and community structure was studied in order to quantify large-scale brain networks in both groups. In comparison to Controls, DLB subjects had decreased global efficiency, clustering, modularity and small-worldness of structural networks (all p < 0.05). Nodal measures showed that DLB subjects also had decreased clustering in bilateral temporal regions and decreased closeness centrality in extensive areas including right middle frontal, left cingulate and bilateral occipital lobe (all false-discovery rate (FDR)-corrected q < 0.05). Whereas four distinct modules could be clearly identified in Controls, DLB showed extensively disorganized modules, including default-mode network and dorsal attentional network. Our results suggest a marked impairment in large-scale brain structural networks in DLB, mirroring functional connectivity networks disruption.

Patterns of cortical grey matter thickness reduction in multiple sclerosis.

ObjectiveTo examine the patterns of cortical gray matter thickness in multiple sclerosis (MS) patients.MethodsSeventy‐four MS patients—clinically isolated syndrome (4%), relapsing–remitting MS (79%), and progressive MS (17%)—and 21 healthy controls (HCs) underwent 1.5 Tesla T1‐weighted 3D MRI examinations to measure brain cortical thickness in a total of 68 regions of interest. Using hierarchical cluster analysis with multivariate cortical thickness data, cortical thickness reduction patterns were cross‐sectionally investigated in MS patients.ResultsThe MS patients were grouped into three major clusters (Clusters 1, 2, and 3). Most of the regional cortical thickness values were equivalent between the HCs and Cluster 1, but decreased in the order of Clusters 2 and 3. Only the thicknesses of the temporal lobe cortices (the bilateral superior and left middle temporal cortex, as well as the left fusiform cortex) were significantly different among Clusters 1, 2, and 3. In contrast, temporal pole thickness reduction was evident exclusively in Cluster 3, which was also characterized by increased lesion loads in the temporal pole and the adjacent juxtacortical white matter, dilatation of the inferior horn of the lateral ventricle, severe whole‐brain volume reduction, and longer disease duration. Although cortical atrophy was significantly more common in the progressive phase, approximately half of the MS patients with the severe cortical atrophy pattern had relapsing–remitting disease.ConclusionCortical thickness reduction patterns in MS are mostly characterized by the degree of temporal lobe cortical atrophy, which may start in the relapsing–remitting phase. Among the temporal lobe cortices, the neurodegenerative change may accelerate in the temporal pole in the progressive phase.

Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

Probing the clinical and brain structural boundaries of bipolar and major depressive disorder

Bipolar disorder (BD) and major depressive disorder (MDD) have both common and distinct clinical features, that pose both conceptual challenges in terms of their diagnostic boundaries and practical difficulties in optimizing treatment. Multivariate machine learning techniques offer new avenues for exploring these boundaries based on clinical neuroanatomical features. Brain structural data were obtained at 3 T from a sample of 90 patients with BD, 189 patients with MDD, and 162 healthy individuals. We applied sparse partial least squares discriminant analysis (s-PLS-DA) to identify clinical and brain structural features that may discriminate between the two clinical groups, and heterogeneity through discriminative analysis (HYDRA) to detect patient subgroups with reference to healthy individuals. Two clinical dimensions differentiated BD from MDD (area under the curve: 0.76, P < 0.001); one dimension emphasized disease severity as well as irritability, agitation, anxiety and flight of ideas and the other emphasized mostly elevated mood. Brain structural features could not distinguish between the two disorders. HYDRA classified patients in two clusters that differed in global and regional cortical thickness, the distribution proportion of BD and MDD and positive family history of psychiatric disorders. Clinical features remain the most reliable discriminant attributed of BD and MDD depression. The brain structural findings suggests that biological partitions of patients with mood disorders are likely to lead to the identification of subgroups, that transcend current diagnostic divisions into BD and MDD and are more likely to be aligned with underlying genetic variation. These results set the foundation for future studies to enhance our understanding of brain–behavior relationships in mood disorders.

Long-term Anabolic–Androgenic Steroid Use Is Associated With Deviant Brain Aging

BackgroundHigh-dose long-term use of anabolic–androgenic steroids (AASs) may cause a range of adverse effects, including brain and cognitive abnormalities. We performed age prediction based on brain scans to test whether prolonged AAS use is associated with accentuated brain aging. MethodsT1-weighted magnetic resonance imaging (3D MPRAGE [magnetization-prepared rapid acquisition gradient-echo]) scans were obtained from male weightlifters with a history of prolonged AAS use (n = 130) or no AAS use (n = 99). We trained machine learning models on combinations of regional brain volumes, cortical thickness, and surface area in an independent training set of 1838 healthy male subjects (18–92 years of age) and predicted brain age for each participant in our study. Including cross-sectional and longitudinal (mean interval = 3.5 years, n = 76) magnetic resonance imaging data, we used linear mixed-effects models to compare the gap between chronological age and predicted brain age (the brain age gap [BAG]) for the two groups and tested for group differences in the rate of change in BAG. We tested for associations between apparent brain aging and AAS use duration, pattern of administration, and dependence. ResultsAAS users had higher BAG compared with weightlifting control subjects, which was associated with dependency and longer history of use. Group differences in BAG could not be explained by other substance use, general cognitive abilities, or depression. While longitudinal analysis revealed no evidence of increased brain aging in the overall AAS group, accelerated brain aging was seen with longer AAS exposure. ConclusionsThe findings suggest that long-term high-dose AAS use may have adverse effects on brain aging, potentially linked to dependency and exaggerated use of AASs.

A performance-based measure of emotion response control: A preliminary MRI study.

Identifying performance-based assessments of emotion regulation is needed for the study of myriad mood and neurological disorders. Color and form responses on the Rorschach Inkblot Method are valid measures of emotion response control, but have not been studied in relation to known neural correlations of emotion regulation. A discrepancy of color (CF+C) greater than form (FC) responses suggests low cognitive control over emotional responses. This preliminary report explores the discrepancy between form-color responses as a correlate of regional cortical thickness. A sample of community-dwelling adults were administered the Rorschach Inkblot Method and participated in a structural MRI scan. Greater middle frontal cortex thickness was associated with a positive discrepancy score [(CF+C) - FC], indicating less emotion response control (rs =0.48, p<0.05); a moderate, non-significant correlation was also observed with insula cortex (rs =0.42, p=0.07).The results provide evidence in support of the Rorschach Inkblot Method as a valid behavioral measure of emotion response control. More specifically, these results support the use of color-related variables included in contemporary evidence-based Rorschach methods. The results are discussed with implications for the study of emotion regulation in mood disorders and sensitivity analyses based on the observed effect sizes are reported to inform future study planning.

Clinically Applicable Quantitative Magnetic Resonance Morphologic Measurements of Grey Matter Changes in the Human Brain.

(1) Purpose: Quantitative magnetic resonance imaging (qMRI) measurements can be used to sensitively estimate brain morphological alterations and may support clinical diagnosis of neurodegenerative diseases (ND). We aimed to establish a normative reference database for a clinical applicable quantitative MR morphologic measurement on neurodegenerative changes in patients; (2) Methods: Healthy subjects (HCs, n = 120) with an evenly distribution between 21 to 70 years and amyotrophic lateral sclerosis (ALS) patients (n = 11, mean age = 52.45 ± 6.80 years), as an example of ND patients, underwent magnetic resonance imaging (MRI) examinations under routine diagnostic conditions. Regional cortical thickness (rCTh) in 68 regions of interest (ROIs) and subcortical grey matter volume (SGMV) in 14 ROIs were determined from all subjects by using Computational Anatomy Toolbox. Those derived from HCs were analyzed to determine age-related differences and subsequently used as reference to estimate ALS-related alterations; (3) Results: In HCs, the rCTh (in 49/68 regions) and the SGMV (in 9/14 regions) in elderly subjects were less than those in younger subjects and exhibited negative linear correlations to age (p < 0.0007 for rCTh and p < 0.004 for SGMV). In comparison to age- and sex-matched HCs, the ALS patients revealed significant decreases of rCTh in eight ROIs, majorly located in frontal and temporal lobes; (4) Conclusion: The present study proves an overall grey matter decline with normal ageing as reported previously. The provided reference may be used for detection of grey matter alterations in neurodegenerative diseases that are not apparent in standard MR scans, indicating the potential of using qMRI as an add-on diagnostic tool in a clinical setting.

Perceived stress, self-efficacy, and the cerebral morphometric markers in binge-drinking young adults

Studies have identified cerebral morphometric markers of binge drinking and implicated cortical regions in support of self-efficacy and stress regulation. However, it remains unclear how cortical structures of self-control play a role in ameliorating stress and alcohol consumption or how chronic alcohol exposure alters self-control and leads to emotional distress. We examined the data of 180 binge (131 men) and 256 non-binge (83 men) drinkers from the Human Connectome Project. We obtained data on regional cortical thickness from the HCP and derived gray matter volumes (GMVs) with voxel-based morphometry. At a corrected threshold, binge relative to non-binge drinking men showed diminished posterior cingulate cortex (PCC) thickness and dorsomedial prefrontal cortex (dmPFC) GMV. PCC thickness and dmPFC GMVs were positively and negatively correlated with self-efficacy and perceived stress, respectively, as assessed with the NIH Emotion Toolbox. Mediation and path analyses to query the inter-relationships between the neural markers and clinical variables showed a best fit of the model with daily drinks → lower PCC thickness and dmPFC GMV → lower self-efficacy → higher perceived stress in men. In contrast, binge and non-binge drinking women did not show significant differences in regional cortical thickness or GMVs. These findings suggest a pathway whereby chronic alcohol consumption alters cortical structures and self-efficacy mediates the effects of cortical structural deficits on perceived stress in men. The findings also suggest the need to investigate multimodal neural markers underlying the interplay between stress, self-control and alcohol use behavior in women.

Cognitive performance shows domain specific associations with regional cortical thickness in multiple sclerosis

Multiple Sclerosis (MS) patients often suffer from significant cognitive impairment. Earlier research has shown relationships between regional cortical atrophy and cognitive deterioration. However, due to a large number of neuropsychological assessments and a heterogenous pattern of cognitive deficits in MS patients, reported associations patterns are also heterogenous. Using an extensive neuropsychological battery of 23 different tasks, we explored domain (attention/information processing, memory, spatial processing, executive functioning) and task-specific associations with regional cortical thickness in a representative sample of MS patients (N = 97). Cortical regions associated with multiple cognitive tasks in the left hemisphere were predominantly located in the inferior insula (attention p < 0.001, memory p = 0.047, spatial processing p = 0.004, executive functioning p = 0.037), the gyrus frontalis superior (attention p = 0.015, memory p = 0.037, spatial processing p = 0.033, executive functioning p = 0.017) and temporal medial (attention p < 0.001, memory two clusters p = 0.016 and p < 0.001, executive functioning p = 0.016). In the right hemisphere, we detected the strongest association in the sulcus interparietalis with five cluster (attention SDMT p = 0.003 and TAP_DA p < 0.001; memory Rey recall p = 0.013 and VLMT verbal learning p = 0.016; spatial processing Rey copy p < 0.001). We replicated parts of our results in an independent sample of 30 mildly disabled MS patients. Moreover, comparisons to 29 healthy controls showed that the regional associations seemed to represent rather pathophysiological dependency than a physiological one. We believe that our results may prove useful in diagnosis and rehabilitation of cognitive impairments and may serve as guidance in future magnetic resonance imaging (MRI) studies.

Regional brain morphology predicts pain relief in trigeminal neuralgia

BackgroundTrigeminal neuralgia, a severe chronic neuropathic pain disorder, is widely believed to be amenable to surgical treatments. Nearly 20% of patients, however, do not have adequate pain relief after surgery. Objective tools for personalized pre-treatment prognostication of pain relief following surgical interventions can minimize unnecessary surgeries and thus are of substantial benefit for patients and clinicians. PurposeTo determine if pre-treatment regional brain morphology-based machine learning models can prognosticate 1 year response to Gamma Knife radiosurgery for trigeminal neuralgia. MethodsWe used a data-driven approach that combined retrospective structural neuroimaging data and support vector machine-based machine learning to produce robust multivariate prediction models of pain relief following Gamma Knife radiosurgery for trigeminal neuralgia. Surgical response was defined as ≥ 75% pain relief 1 year post-treatment. We created two prediction models using pre-treatment regional brain gray matter morphology (cortical thickness or surface area) to distinguish responders from non-responders to radiosurgery. Feature selection was performed through sequential backwards selection algorithm. Model out-of-sample generalizability was estimated via stratified 10-fold cross-validation procedure and permutation testing. ResultsIn 51 trigeminal neuralgia patients (35 responders, 16 non-responders), machine learning models based on pre-treatment regional brain gray matter morphology (14 regional surface areas or 13 regional cortical thicknesses) provided robust a priori prediction of surgical response. Cross-validation revealed the regional surface area model was 96.7% accurate, 100.0% sensitive, and 89.1% specific while the regional cortical thickness model was 90.5% accurate, 93.5% sensitive, and 83.7% specific. Permutation testing revealed that both models performed beyond pure chance (p < 0.001). The best predictor for regional surface area model and regional cortical thickness model was contralateral superior frontal gyrus and contralateral isthmus cingulate gyrus, respectively. ConclusionsOur findings support the use of machine learning techniques in subsequent investigations of chronic neuropathic pain. Furthermore, our multivariate framework provides foundation for future development of generalizable, artificial intelligence-driven tools for chronic neuropathic pain treatments.

Understanding the role of APOE Gene Polymorphisms in Minimal Atrophy Alzheimer’s Disease by mixture of expert models

Alzheimer’s disease (AD) is a heterogeneous disease. Exploring the characteristics of each AD subtype is the key to disentangling the heterogeneity. Minimal atrophy AD (MAD) is a common AD subtype that yields conflicting results. In order to evaluate this aspect across relatively large heterogeneous AD populations, a total of 192 AD and 228 cognitively normal (CN) subjects were processed by the automated segmentation scheme FreeSurfer, which generates regional cortical thickness measures. A machine learning driven approach, the mixture of expert models, which combines unsupervised modeling of mixtures of distributions with supervised learning of classifiers, was applied to approximates the non-linear boundary between AD and CN subjects with a piece-wise linear boundary. Multiple cortical thicknes patterns of AD were discovered, which includes: bilateral parietal/frontal atrophy AD, left temporal dominant atrophy AD, MAD, and diffuse atrophy AD. MAD had the highest proportions of ApoE4 and ApoE2. Further analysis revealed that ApoE genotype, disease stage and their interactions can partially explain the conflicting observations in MAD.

Regional Associations of Cortical Thickness With Gait Variability: The Tasmanian Study of Cognition and Gait

Gait variability is a marker of cognitive decline. However, there is limited understanding of the cortical regions associated with gait variability. We examined associations between regional cortical thickness and gait variability in a population-based sample of older people without dementia. Participants (n=350, mean age 71.9±7.1) were randomly selected from the electoral roll. Variability in step time, step length, step width and double support time (DST) were calculated as the standard deviation of each measure, obtained from the GAITRite walkway. MRI scans were processed through FreeSurfer to obtain cortical thickness of 68 regions. Bayesian regression was used to determine regional associations of mean cortical thickness and thickness ratio (regional thickness/overall mean thickness) with gait variability. Smaller overall cortical thickness was only associated with greater step width and step time variability. Smaller mean thickness in widespread regions important for sensory, cognitive and motor functions were associated with greater step width and step time variability. In contrast, smaller thickness in a few frontal and temporal regions were associated with DST variability and the right cuneus was associated with step length variability. Smaller thickness ratio in frontal and temporal regions important for motor planning, execution and sensory function and, greater thickness ratio in the anterior cingulate was associated with greater variability in all measures. Examining individual cortical regions is important in understanding the relationship between gray matter and gait variability. Cortical thickness ratio highlights that smaller regional thickness relative to global thickness may be important for the consistency of gait.

Adiposity Is Positively Associated With AD-Signature Cortical Thickness in Older Adults

Mid-life obesity is associated with a higher risk for Alzheimer’s disease (AD). However, this association is attenuated or even reversed in late-life, when weight loss may be a preclinical sign of AD. While neuropathological changes likely occur alongside aging-related changes in body composition, this has not been largely investigated. We aimed to determine the association between adiposity and a specific pattern of reduced cortical thickness associated with AD risk and progression. Global and regional adiposity (via dual-energy x-ray absorptiometry) and AD-signature cortical thickness (via surface-based cortical analysis of 3T brain MRI scans) were measured in 35 middle-aged and older adults from the Wake Forest Alzheimer’s Disease Clinical Core (mean age: 69.4±7.8 years, 80% female, 91% White, 29% cognitively impaired). Partial correlations adjusted for age, sex, and cognitive status were examined overall and stratified by age (0.59, p≤0.05). No significant associations were observed in middle-aged adults. These findings suggest that AD-related cortical thinning may be accompanied by a global reduction in body fat among older adults.

Association between visceral fat amount and brain cortical thinning in the community‐dwelling elderly population

AbstractBackgroundDespite emerging evidence suggesting that visceral fat may play a major role in the neurotoxic effect of obesity, no study has investigated the association between visceral fat amount and cortical thickness in the elderly. We examined the association of abdominal fat amount with cortical thickness and subcortical structures in the elderly.MethodCommunity‐dwelling individuals (≥60 years of age) without known neurological diseases (n=316) were included. Areas of subcutaneous fat and visceral fat were estimated from computed tomography scan. Regional cortical thicknesses and subcortical volumes were obtained by analyzing brain 3T magnetic resonance imaging. A generalized additive model was built to explore non‐linearity between abdominal fat amount and cortical thickness. A generalized linear model was used to explore the brain imaging markers associated with an increase in abdominal fat amount (quintiles used for cortical thickness).ResultThere were inverted U‐shape relationships of visceral fat amount with global (p=0.02), frontal (p=0.02), temporal (p=0.02), and parietal thicknesses (p&lt;0.001). The quintile 5 (the highest) group had significantly thinner cortices compared with the quintile 3 group in the global (β=‐0.04, p=0.004), parietal (β=‐0.04, p=0.01), temporal lobes (β=‐0.05, p=0.002), cingulate (β=‐0.06, p=0.01), and insula (β=‐0.06, p=0.02). The higher amount of visceral fat was significantly associated with the smaller volume of the pallium (β=‐0.66, p=0.01) and putamen (β=‐1.36, p=0.03). Most of the associations between subcutaneous fat amount and the brain imaging markers were not significant.ConclusionWe found an inverted U shaped relationship between visceral fat amount and cortical thickness in elderly individuals. Future studies are needed to elucidate causal relationships and explore other factors which may be confounders.

Amyloid‐β deposition in cognitively normal oldest‐old is associated with cortical thinning and faster memory decline

AbstractBackgroundThe Alzheimer’s disease (AD) pathological cascade is hypothesized to start with the accumulation of amyloid‐β (Aβ). However, the precise effect of Aβ deposition on cognitive decline in the oldest‐old remains controversial, since very old individuals can have intact cognition despite abnormal AD biomarkers. Here we studied, in cognitively normal individuals of 90 years and older, the impact of Aβ on structural brain integrity and the association of Aβ and structural brain integrity on decline over time in memory functioning.MethodFifty‐seven cognitively normal individuals (age mean ± sd = 92.7 ± 2.9) were selected from the EMIF‐AD 90+ study. Aβ status was determined by visual reads on [18F]‐flutemetamol PET (normal = Aβ‐, abnormal = Aβ+); cortical thickness and hippocampal volume were quantified on structural MRI with FreeSurfer and FSL, respectively. Cortical thickness was computed according to the Desikan‐Killany atlas and averaged across hemispheres. Hippocampal volume was normalized for intracranial volume. Memory performance was evaluated using a composite score of the CERAD (delayed recall), Logical Memory (delayed recall), Rey Complex Figure (delayed copy), and the Visual Association Test, that were repeated after 20 months (n = 43). Effects of Aβ status, regional cortical thickness, hippocampal volume, time, and their interactions on memory function were assessed with linear mixed models, adjusted for age and sex.ResultRoughly one out of three (n = 19; 33%) individuals had an abnormal amyloid PET (Table 1). Compared to Aβ‐, those with Aβ+ showed at baseline a thinner parahippocampal and medial orbitofrontal cortex (p&lt;.05; Figure 1), while hippocampal volume did not differ. Over time, Aβ+ individuals showed a steeper decline (β ± SE = ‐.27 ± .09; p&lt;.01;) on memory performance than Aβ‐ (Figure 1). Faster memory decline was also predicted by cortical thinning in predominantly temporal regions in the whole group (Figure 1).ConclusionIn the oldest‐old with initially intact cognition, Aβ pathology was associated with a thinner cortex and faster decline in memory performance. These results suggest that Aβ abnormality, even in the oldest old with apparent high reserve and maintenance mechanisms, is indicative of active neurodegeneration. Other pathologies may also contribute to decline in the oldest old as a thinner temporal lobe predicted decline in memory irrespective of Aβ pathology.

Amyloid‐β deposition in cognitively normal oldest‐old is associated with cortical thinning and faster memory decline

AbstractBackgroundThe Alzheimer’s disease (AD) pathological cascade is hypothesized to start with the accumulation of amyloid‐β (Aβ). However, the precise effect of Aβ deposition on cognitive decline in the oldest‐old remains controversial, since very old individuals can have intact cognition despite abnormal AD biomarkers. Here we studied, in cognitively normal individuals of 90 years and older, the impact of Aβ on structural brain integrity and the association of Aβ and structural brain integrity on decline over time in memory functioning.MethodFifty‐seven cognitively normal individuals (age mean±sd = 92.7±2.9) were selected from the EMIF‐AD 90+ study. Aβ status was determined by visual reads on [18F]‐flutemetamol PET (normal=Aβ‐, abnormal=Aβ+); cortical thickness and hippocampal volume were quantified on structural MRI with FreeSurfer and FSL, respectively. Cortical thickness was computed according to the Desikan‐Killany atlas and averaged across hemispheres. Hippocampal volume was normalized for intracranial volume. Memory performance was evaluated using a composite score of the CERAD (delayed recall), Logical Memory (delayed recall), Rey Complex Figure (delayed copy), and the Visual Association Test, that were repeated after 20 months (n=43). Effects of Aβ status, regional cortical thickness, hippocampal volume, time, and their interactions on memory function were assessed with linear mixed models, adjusted for age and sex.ResultRoughly one out of three (n=19; 33%) individuals had an abnormal amyloid PET (Table1). Compared to Aβ‐, those with Aβ+ showed at baseline a thinner parahippocampal and medial orbitofrontal cortex (p&lt;.05; Fig.1), while hippocampal volume did not differ. Over time, Aβ+ individuals showed a steeper decline (β±SE=‐.27±.09; p&lt;.01;) on memory performance than Aβ‐ (Fig.1). Faster memory decline was also predicted by cortical thinning in predominantly temporal regions in the whole group (Fig.1).ConclusionIn the oldest‐old with initially intact cognition, Aβ pathology was associated with a thinner cortex and faster decline in memory performance. These results suggest that Aβ abnormality, even in the oldest old with apparent high reserve and maintenance mechanisms, is indicative of active neurodegeneration. Other pathologies may also contribute to decline in the oldest old as a thinner temporal lobe predicted decline in memory irrespective of Aβ pathology.

Serum cortisol, cerebral amyloidosis, and neurodegeneration: A longitudinal study

AbstractBackgroundAlthough elevated blood cortisol has been repeatedly associated with Alzheimer`s disease (AD) and related cognitive decline, the pathological links underlying the association remain poorly understood. In this context, we aimed to investigate the relationship between serum cortisol and AD neuroimaging markers including amyloid beta protein (Aβ) deposition, tau deposition, AD‐signature region cerebral glucose metabolism (AD‐CM), AD‐signature region cortical thickness (AD‐CT), and adjusted hippocampal volume (HVa).MethodThis study was part of the of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE), an ongoing prospective cohort study. A total of 503 middle‐aged and elderly adults, including cognitively normal adults and individuals with mild cognitive impairment and AD dementia, underwent comprehensive clinical and neuropsychological assessments, 11C‐Pittsburgh compound B (PiB)‐PET, 18F‐deoxyglucose (FDG)‐PET, MRI, and serum cortisol level quantification at baseline and 2 years later. A subset of subjects also received 18F‐AV‐1451 PET during the follow‐up evaluation.ResultAt baseline, a significant positive association was found between serum cortisol level and global cerebral Aβ deposition after controlling for the effects of potential confounders (i.e., age, sex, APOE4 status, cognitive status, vascular risk, and depression). In addition, cortisol level showed significant inverse association with AD‐CM even after controlling for global Aβ retention as well as the confounders. There was no significant relationship between cortisol and cerebral tau deposition. In regard of longitudinal changes of AD markers, baseline cortisol level also had significant positive association with increase of cerebral Aβ deposition over 2 years, but not with changes of any neurodegeneration markers.ConclusionThe findings indicate that high serum cortisol contribute to AD processes through pathological cerebral Aβ deposition. Additionally, cortisol appears to directly affect neurodegeneration in AD‐signature brain regions via Aβ‐independent mechanisms.

Personalized estimates of morphometric similarity in bipolar disorder and schizophrenia

Bipolar disorder and schizophrenia are associated with brain morphometry alterations. This study investigates inter-individual variability in brain structural profiles, both within diagnostic groups and between patients and healthy individuals. Brain morphometric measures from three independent samples of patients with schizophrenia (n = 168), bipolar disorder (n = 122), and healthy individuals (n = 180) were modeled as single vectors to generated individualized profiles of subcortical volumes and regional cortical thickness. These profiles were then used to compute a person-based similarity index (PBSI) for subcortical volumes and for regional cortical thickness, to quantify the within-group similarity of the morphometric profile of each individual to that of the other participants in the same diagnostic group. There was no effect of diagnosis on the PBSI for subcortical volumes. In contrast, compared to healthy individuals, the PBSI for cortical thickness was lower in patients with schizophrenia (effect size = 0.4, p ≤ 0.0002), but not in patients with bipolar disorder. The results were robust and reproducible across samples. We conclude that disease mechanisms for these disorders produce modest inter-individual variations in brain morphometry that should be considered in future studies attempting to cluster patients in subgroups.

Plasma phosphorylated tau181 and neurodegeneration in Alzheimer's disease.

We examined if plasma phosphorylated tau is associated with neurodegeneration in Alzheimer’s disease. We investigated 372 cognitively unimpaired participants, 554 mild cognitive impairment patients, and 141 Alzheimer’s disease dementia patients. Tau phosphorylated at threonine 181, regional cortical thickness (using magnetic resonance imaging) and hypometabolism (using fluorodeoxyglucose positron emission tomography) were measured longitudinally. High plasma tau was associated with hypometabolism and cortical atrophy at baseline and over time, and longitudinally increased tau was associated with accelerated atrophy, but these associations were only observed in Aβ‐positive participants. Plasma phosphorylated tau may identify and track processes linked to neurodegeneration in Alzheimer’s disease.