Hippocampal volumes among older Indian adults: Comparison with Alzheimer's disease and mild cognitive impairment

A comparison of story-recall metrics to predict hippocampal volume in older adults with and without cognitive impairment

Objective: Process-based scores of episodic memory tests, such as the recency ratio (Rr), have been found to compare favourably to, or to be better than, most conventional or "traditional" scores employed to estimate memory ability in older individuals (Bock et al., 2021; Bruno et al., 2019). We explored the relationship between process-based scores and hippocampal volume in older adults, while comparing process-based to traditional story recall-derived scores, to examine potential differences in their predictive abilities. Methods: We analysed data from 355 participants extracted from the WRAP and WADRC databases, who were classified as cognitively unimpaired, or exhibited mild cognitive impairment (MCI) or dementia. Story Recall was measured with the Logical Memory Test (LMT) from the Weschler Memory Scale Revised, collected within twelve months of the magnetic resonance imaging scan. Linear regression analyses were conducted with left or right hippocampal volume (HV) as outcomes separately, and with Rr, Total ratio, Immediate LMT, or Delayed LMT scores as predictors, along with covariates. Results: Higher Rr and Tr scores significantly predicted lower left and right HV, while Tr showed the best model fit of all, as indicated by AIC. Traditional scores, Immediate LMT and Delayed LMT, were significantly associated with left and right HV, but were outperformed by both process-based scores for left HV, and by Tr for right HV. Conclusions: Current findings show the direct relationship between hippocampal volume and all the LMT scores examined here, and that process-based scores outperform traditional scores as markers of hippocampal volume.

Hippocampal Volume in Children with Attention Deficit Hyperactivity Disorder and Speech and Language Delay

Introduction

Hippocampus is a complex brain structure located deep in the temporal lobes of the brain. The structure has been implicated in several disorders related to cognition. Reports are emerging of its involvement in attention deficit hyperactivity disorder (ADHD). The current study was planned to assess the volume of the hippocampus in children with ADHD and speech and language delay with normal birth history using magnetic resonance imaging (MRI) of the brain.

Material and Methods

MRI brain of 12 children (age range = 3-6 years) and 22 controls with clinical diagnosis of ADHD as per Diagnostic and Statistical Manual-5 were obtained in oblique coronal sequence (T1 weighted). The entire hippocampus formation was outlined manually using Image-J software available freely from www.freesurfer.com. Results were expressed as volume cubic millimeters ± SD.

Results

Volumes of the hippocampi of children with ADHD were 2450.2 ± 667 mm3 (R) and 2505.8 ± 878.5 mm3 (L), respectively. The mean volume (bilateral) of the cases was 2478 ± 772.75 mm3. The right hippocampal volume of the controls was 3255.8 ± 1374.3 mm3 (R) and that of the left side was 3159.3 ± 1451 (L) mm3, respectively.

Conclusion

Current study reported a substantial shrinkage (23%) of the left and right hippocampus in children with ADHD compared to controls.

Metabolic Asymmetry Relates to Clinical Characteristics and Brain Network Abnormalities in Alzheimer's Disease

BACKGROUND

Metabolic asymmetry has been observed in Alzheimer's disease (AD), but different studies have inconsistent viewpoints.

OBJECTIVE

To analyze the asymmetry of cerebral glucose metabolism in AD and investigate its clinical significance and potential metabolic network abnormalities.

METHODS

Standardized uptake value ratios (SUVRs) were obtained from 18F-FDG positron emission tomography (PET) images of all participants, and the asymmetry indices (AIs) were calculated according to the SUVRs. AD group was divided into left/right-dominant or bilateral symmetric hypometabolism (AD-L/AD-R or AD-BI) when more than half of the AIs of the 20 regions of interest (ROIs) were < -2SD, >2SD, or between±1SD. Differences in clinical features among the three AD groups were compared, and the abnormal network characteristics underlying metabolic asymmetry were explored.

RESULTS

In AD group, the proportions of AD-L, AD-R, and AD-BI were 28.4%, 17.9%, and 18.5%, respectively. AD-L/AD-R groups had younger age of onset and faster rate of cognitive decline than AD-BI group (p < 0.05). The absolute values of AIs in half of the 20 ROIs became higher at follow-up than at baseline (p < 0.05). Compared with those in AD-BI group, metabolic connection strength of network, global efficiency, cluster coefficient, degree centrality and local efficiency were lower, but shortest path length was longer in AD-L and AD-R groups (p < 0.05).

CONCLUSION

Asymmetric and symmetric hypometabolism may represent different clinical subtypes of AD, which may provide a clue for future studies on the heterogeneity of AD and help to optimize the design of clinical trials.

Atrophy asymmetry in hippocampal subfields in patients with Alzheimer's disease and mild cognitive impairment

Volumetric analysis of hippocampal subfields and their asymmetry assessment recently has been useful biomarkers in neuroscience. In this study, hippocampal subfields atrophy and pattern of their asymmetry in the patient with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were evaluated. MRI images of 20 AD patients, 20 MCI patients, and 20 healthy control (HC) were selected. The volumes of hippocampal subfields were extracted automatically using Freesurfer toolkit. The subfields asymmetry index (AI) and laterality ([Formula: see text]) were also evaluated. Analysis of covariance was used to compare the subfields volume between three patient groups (age and gender as covariates). We used ANOVA (P < 0.05) test for multiple comparisons with Bonferroni's post hoc correction method. Hippocampal subfields volume in AD patients were significantly lower than HC and MCI groups (P < 0.02); however, no significant difference was observed between MCI and HC groups. The asymmetry index (AI) in some subfields was significantly different between AD and MCI, as well as between AD and HC, while there was not any significant difference between MCI groups with HC. In all three patient groups, rightward laterality ([Formula: see text]) was seen in several subfields except subiculum, presubiculum, and parasubiculum, while in AD patient, rightward lateralization slightly decrease. Hippocampal subfields asymmetry can be used as a quantitative biomarker in neurocognitive disorders. In this study, it was observed that the asymmetry index of some subfields in AD is significantly different from MCI. In AD, patient rightward laterality was less MCI an HC group.

Sulfiredoxin-1 blood mRNA expression levels negatively correlate with hippocampal atrophy and cognitive decline

Introduction: Cognitive decline, correlating with hippocampal atrophy, characterizes several neurodegenerative disorders having a background of low-level chronic inflammation and oxidative stress.

Methods: In this cross-sectional study, we examined how cognitive decline and hippocampal subfields volume are associated with the expression of redox and inflammatory genes in peripheral blood. We analyzed 34 individuals with different cognitive scores according to Mini-Mental State Examination, corrected by age and education (adjMMSE). We identified a group presenting cognitive decline (CD) with adjMMSE<27 (n=14) and a normal cognition (NC) group with adjMMSE≥27 (n=20). A multiparametric approach, comprising structural magnetic resonance imaging measurement of different hippocampal segments and blood mRNA expression of redox and inflammatory genes was applied.

Results: Our findings indicate that hippocampal segment volumes correlate positively with adjMMSE and negatively with the blood transcript levels of 19 genes, mostly redox genes correlating especially with the left subiculum and presubiculum. A strong negative correlation between hippocampal subfields atrophy and Sulfiredoxin-1 ( SRXN1) redox gene was emphasized.

Conclusions: Concluding, these results suggest that SRXN1 might be a valuable candidate blood biomarker for non-invasively monitoring the evolution of hippocampal atrophy in CD patients.

Magnetic Resonance Imaging Characterization of the Hippocampi in Temporal Lobe Epilepsy: Correlation of Volumetry and Apparent Diffusion Coefficient with Laterality and Duration of Seizures

Background and Purpose It is estimated that hippocampal damage is seen in 50 to 70% of patients with temporal lobe epilepsy (TLE). Although most magnetic resonance imaging (MRI) studies are adequate to detect gross hippocampal atrophy, subtle changes that may characterize early disease in TLE, such as visually nonappreciable volume loss, may often be missed if objective volumetric analysis is not undertaken. Materials and Methods We conducted a hospital-based prospective analytical study in which 40 patients with partial seizures of temporal lobe origin were included and their hippocampal volumes (HVs) were determined by manual volumetric analysis. The findings were recorded and correlated with the side of seizure and its duration. The quantitative assessment was allotted different grades accordingly. Also, the apparent diffusion coefficient (ADC) values of bilateral hippocampi were estimated and their correlation with the side of seizure was determined. Results Most patients in the study were in the age group of 11 to 20 years (37.5%). In total, 57.5% had seizures for a period of 1 to 5 years. While 67.5% ( n = 27) had seizure on the right, 32.5% ( n = 13) had on the left. The mean HV estimated on the right and left were correlated with the side of seizure and found to be statistically significant ( p < 0.001 in those with right-sided seizures and p = 0.02 in those with left-sided seizures). Simultaneously the ADC values estimated were found to correlate with the laterality of seizures with a statistical difference ( p < 0.01) . Duration of seizures however did not show a positive correlation with the HV. Conclusion MRI with quantitative estimation of HV and ADC values can depict the presence and laterality in TLE with accuracy rates that exceed those achieved by visual inspection alone. Thus, quantitative MRI provides a useful means for translating volumetric analysis into clinical practice.

Tetrahydroxy stilbene glycoside alleviated inflammatory damage by mitophagy via AMPK related PINK1/Parkin signaling pathway

Alzheimer's disease (AD) is an irreversible neurodegenerative brain disorder with complex pathogenesis. The fibrillar peptide β-amyloid (Aβ) has a chief function in the pathogenesis of AD. Emerging evidence has indicated that there is a tight relationship between inflammation, mitochondrial dysfunction and Aβ formation. 2,3,5,4'-Tetrahydroxystilbene-2-O-β-D-glucoside (TSG) is one of the main active components extracted from Polygonum multiflorum. Recent research corroborated the beneficial roles of TSG in alleviating the learning and memory of AD models. Unfortunately, the underlying mechanism of TSG remains poorly elucidated. The purpose of the present study was to investigate the effects of TSG on LPS/ATP and Aβ_25-35-induced inflammation in microglia and neurons and its underlying molecular mechanisms. Our results found that treatment with TSG significantly attenuated the secretion of inflammatory cytokines, reduced NLRP3 inflammasome, and regulated mitophagy. TSG efficiently alleviated LPS-induced inflammatory response by inhibiting the NLRP3 signaling pathway both in microglia and neuron. Meanwhile, TSG promoted autophagy involved in the AMPK/PINK1/Parkin signaling pathway, which may contribute to the protective activity. Additional mechanistic investigations to evaluate the dependence of the neuroprotective role of TSG on PINK1 revealed that a lack of PINK1 inhibited autophagy, especially mitophagy in microglia. Importantly, knockdown of PINK1 or Parkin by siRNA or CRISPR/Cas9 system abolished the protective effects of TSG. In conclusion, these phenomena suggested that TSG prevented LPS/ATP and Aβ-induced inflammation via AMPK/PINK1/Parkin-dependent enhancement of mitophagy. We found the neuroprotective effect of TSG, suggesting it may be beneficial for AD prevention and treatment by suppressing the activation of inflammation.

Brain Network and Abnormal Hemispheric Asymmetry Analyses to Explore the Marginal Differences in Glucose Metabolic Distributions Among Alzheimer's Disease, Parkinson's Disease Dementia, and Lewy Body Dementia

Facilitating accurate diagnosis and ensuring appropriate treatment of dementia subtypes, including Alzheimer's disease (AD), Parkinson's disease dementia (PDD), and Lewy body dementia (DLB), is clinically important. However, the differences in glucose metabolic distribution among these three dementia subtypes are minor, which can result in difficulties in diagnosis by visual assessment or traditional quantification methods. Here, we explored this issue using novel approaches, including brain network and abnormal hemispheric asymmetry analyses. We generated 18F-labeled fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) images from patients with AD, PDD, and DLB, and healthy control (HC) subjects (n = 22, 18, 22, and 22, respectively) from Huashan hospital, Shanghai, China. Brain network properties were measured and between-group differences evaluated using graph theory. We also calculated and explored asymmetry indices for the cerebral hemispheres in the four groups, to explore whether differences between the two hemispheres were characteristic of each group. Our study revealed significant differences in the network properties of the HC and AD groups (small-world coefficient, 1.36 vs. 1.28; clustering coefficient, 1.48 vs. 1.59; characteristic path length, 1.57 vs. 1.64). In addition, differing hub regions were identified in the different dementias. We also identified rightward asymmetry in the hemispheric brain networks of patients with AD and DLB, and leftward asymmetry in the hemispheric brain networks of patients with PDD, which were attributable to aberrant topological properties in the corresponding hemispheres.

Analysis of structural brain MRI and multi-parameter classification for Alzheimer's disease

Incorporating with machine learning technology, neuroimaging markers which extracted from structural Magnetic Resonance Images (sMRI), can help distinguish Alzheimer's Disease (AD) patients from Healthy Controls (HC). In the present study, we aim to investigate differences in atrophic regions between HC and AD and apply machine learning methods to classify these two groups. T1-weighted sMRI scans of 158 patients with AD and 145 age-matched HC were acquired from the ADNI database. Five kinds of parameters (i.e. cortical thickness, surface area, gray matter volume, curvature and sulcal depth) were obtained through the preprocessing steps. The recursive feature elimination (RFE) method for support vector machine (SVM) and leave-one-out cross validation (LOOCV) were applied to determine the optimal feature dimensions. Each kind of parameter was trained by SVM algorithm to acquire a classifier, which was used to classify HC and AD ultimately. Moreover, the ROC curves were depicted for testing the classifiers' performance and the SVM classifiers of two-dimensional spaces took the top two important features as classification features for separating HC and AD to the maximum extent. The results showed that the decreased cortical thickness and gray matter volume dramatically exhibited the trend of atrophy. The key differences between AD and HC existed in the cortical thickness and gray matter volume of the entorhinal cortex and medial orbitofrontal cortex. In terms of classification results, an optimal accuracy of 90.76% was obtained via multi-parameter combination (i.e. cortical thickness, gray matter volume and surface area). Meanwhile, the receiver operating characteristic (ROC) curves and area under the curve (AUC) were also verified multi-parameter combination could reach a better classification performance (AUC=0.94) after the SVM-RFE method. The results could be well prove that multi-parameter combination could provide more useful classified features from multivariate anatomical structure than single parameter. In addition, as cortical thickness and multi-parameter combination contained more important classified information with fewer feature dimensions after feature selection, it could be optimum to separate HC from AD to take the top two important features of them to construct SVM classifiers in two-dimensional space. The proposed work is a promising approach suggesting an important role for machine-learning based diagnostic image analysis for clinical practice.

MRI Asymmetry Index of Hippocampal Subfields Increases Through the Continuum From the Mild Cognitive Impairment to the Alzheimer's Disease

Objective: It is well-known that the hippocampus presents significant asymmetry in Alzheimer's disease (AD) and that difference in volumes between left and right exists and varies with disease progression. However, few works investigated whether the asymmetry degree of subfields of hippocampus changes through the continuum from Mild Cognitive Impairment (MCI) to AD. Thus, aim of the present work was to evaluate the Asymmetry Index (AI) of hippocampal substructures as possible MRI biomarkers of Dementia. Moreover, we aimed to assess whether the subfields presented peculiar differences between left and right hemispheres. We also investigated the relationship between the asymmetry magnitude in hippocampal subfields and the decline of verbal memory as assessed by Rey's auditory verbal learning test (RAVLT). Methods: Four-hundred subjects were selected from ADNI, equally divided into healthy controls (HC), AD, stable MCI (sMCI), and progressive MCI (pMCI). The structural baseline T1s were processed with FreeSurfer 6.0 and volumes of whole hippocampus (WH) and 12 subfields were extracted. The AI was calculated as: (|Left-Right|/(Left+Right))*100. ANCOVA was used for evaluating AI differences between diagnoses, while paired t-test was applied for assessing changes between left and right volumes, separately for each group. Partial correlation was performed for exploring relationship between RAVLT summary scores (Immediate, Learning, Forgetting, Percent Forgetting) and hippocampal substructures AI. The statistical threshold was Bonferroni corrected p < 0.05/13 = 0.0038. Results: We found a general trend of increased degree of asymmetry with increasing severity of diagnosis. Indeed, AD presented the higher magnitude of asymmetry compared with HC, sMCI and pMCI, in the WH (AI mean 5.13 ± 4.29 SD) and in each of its twelve subfields. Moreover, we found in AD a significant negative correlation (r = -0.33, p = 0.00065) between the AI of parasubiculum (mean 12.70 ± 9.59 SD) and the RAVLT Learning score (mean 1.70 ± 1.62 SD). Conclusions: Our findings showed that hippocampal subfields AI varies differently among the four groups HC, sMCI, pMCI, and AD. Moreover, we found-for the first time-that hippocampal substructures had different sub-patterns of lateralization compared with the whole hippocampus. Importantly, the severity in learning rate was correlated with pathological high degree of asymmetry in parasubiculum of AD patients.

Impact of the Relationship of Stress and the Immune System in the Appearance of Alzheimer's Disease

The understanding of how the immune system works, as well as its relationship with the stress level, seems to be important at the start of the Alzheimer's disease (AD). To analyze this, immunoglobulin A (IgA) and cortisol in saliva were measured using ELISA in patients with mild AD and healthy volunteers, and the production of both biomarkers was compared and correlated. In participants without AD, IgA was higher when cortisol was lower, and the opposite happened in participants with AD, with the quantification in saliva being a suitable method to determine it.

Tetrahydroxy stilbene glycoside (TSG) antagonizes Aβ-induced hippocampal neuron injury by suppressing mitochondrial dysfunction via Nrf2-dependent HO-1 pathway

Amyloid-beta peptide (Aβ) ranks as a pivotal cause of Alzheimer's disease (AD), a common devastating dementia form in elderly. Recent research corroborated the beneficial roles of tetrahydroxystilbene glucoside (TSG) in alleviating the learning and memory of AD model and aged mice. Unfortunately, the underlying mechanism remains poorly elucidated. Here, treatment with non-toxic TSG dose-dependently antagonized Aβ-induced cytotoxic death in hippocampal neuronal cells by increasing cell viability and decreasing cell apoptosis. Furthermore, TSG also alleviated cell oxidative stress injury in response to Aβ by attenuating lactate dehydrogenase (LDH) release, ROS levels and MDA leakage. Importantly, TSG administration abrogated Aβ-triggered loss of mitochondrial membrane potential (Δy_m), release of cytochrome c from mitochondrial to cytosol, increase in caspase-3 activity and pro-apoptotic protein Bax, and decrease in Bcl-2 protein, indicating that TSG could rescue mitochondrial dysfunctions of neuron cells under adverse Aβ condition. Subsequently, TSG induced the activation of Nrf2-HO-1 pathway. Importantly, blocking this pathway by si-Nrf2 transfection or HO-1 antagonist ZnPP notably muted the cytoprotective effects of TSG on neuronal cell cytotoxic injury upon Aβ stimulation. Together, this research substantiated a new mechanism that TSG protectively antagonized Aβ-induced hippocampal neuronal cell damage by restoring mitochondrial function via Nrf2-HO-1 pathway, implying a promising candidate against neurodegenerative diseases including AD.

The Abnormality of Topological Asymmetry between Hemispheric Brain White Matter Networks in Alzheimer's Disease and Mild Cognitive Impairment

A large number of morphology-based studies have previously reported a variety of regional abnormalities in hemispheric asymmetry in Alzheimer’s disease (AD). Recently, neuroimaging studies have revealed changes in the topological organization of the structural network in AD. However, little is known about the alterations in topological asymmetries. In the present study, we used diffusion tensor image tractography to construct the hemispheric brain white matter networks of 25 AD patients, 95 mild cognitive impairment (MCI) patients, and 48 normal control (NC) subjects. Graph theoretical approaches were then employed to estimate hemispheric topological properties. Rightward asymmetry in both global and local network efficiencies were observed between the two hemispheres only in AD patients. The brain regions/nodes exhibiting increased rightward asymmetry in both AD and MCI patients were primarily located in the parahippocampal gyrus and cuneus. The observed rightward asymmetry was attributed to changes in the topological properties of the left hemisphere in AD patients. Finally, we found that the abnormal hemispheric asymmetries of brain network properties were significantly correlated with memory performance (Rey’s Auditory Verbal Learning Test). Our findings provide new insights into the lateralized nature of hemispheric disconnectivity and highlight the potential for using hemispheric asymmetry of brain network measures as biomarkers for AD.

Correlation between hippocampal volumes and medial temporal lobe atrophy in patients with Alzheimer's disease

Introduction:

Hippocampus undergoes atrophy in patients with Alzheimer's disease (AD). Calculation of hippocampal volumes can be done by a variety of methods using T1-weighted images of magnetic resonance imaging (MRI) of the brain. Medial temporal lobes atrophy (MTL) can be rated visually using T1-weighted MRI brain images. The present study was done to see if any correlation existed between hippocampal volumes and visual rating scores of the MTL using Scheltens Visual Rating Method.

Materials and Methods:

We screened 84 subjects presented to the Department of Neurology of a Tertiary Care Hospital and enrolled forty subjects meeting the National Institute of Neurological and Communicative Disorders and Stroke, AD related Disease Association criteria. Selected patients underwent MRI brain and T1-weighted images in a plane perpendicular to long axis of hippocampus were obtained. Hippocampal volumes were calculated manually using a standard protocol. The calculated hippocampal volumes were correlated with Scheltens Visual Rating Method for Rating MTL. A total of 32 cognitively normal age-matched subjects were selected to see the same correlation in the healthy subjects as well. Sensitivity and specificity of both methods was calculated and compared.

Results:

There was an insignificant correlation between the hippocampal volumes and MTL rating scores in cognitively normal elderly (n = 32; Pearson Correlation coefficient = 0.16, P > 0.05). In the AD Group, there was a moderately strong correlation between measured hippocampal volumes and MTL Rating (Pearson's correlation coefficient = −0.54; P < 0.05. There was a moderately strong correlation between hippocampal volume and Mini-Mental Status Examination in the AD group. Manual delineation was superior compared to the visual method (P < 0.05).

Conclusions:

Good correlation was present between manual hippocampal volume measurements and MTL scores. Sensitivity and specificity of manual measurement of hippocampus was higher compared to visual rating scores for MTL in patients with AD.