Hippocampal Volume Research Articles

Classification of Mild Cognitive Impairment and Alzheimer’s Disease Using Manual Motor Measures

Introduction: Manual motor problems have been reported in mild cognitive impairment (MCI) and Alzheimer’s disease (AD), but the specific aspects that are affected, their neuropathology, and potential value for classification modeling is unknown. The current study examined if multiple measures of motor strength, dexterity, and speed are affected in MCI and AD, related to AD biomarkers, and are able to classify MCI or AD. Methods: Fifty-three cognitively normal (CN), 33 amnestic MCI, and 28 AD subjects completed five manual motor measures: grip force, Trail Making Test A, spiral tracing, finger tapping, and a simulated feeding task. Analyses included (1) group differences in manual performance; (2) associations between manual function and AD biomarkers (PET amyloid β, hippocampal volume, and APOE ε4 alleles); and (3) group classification accuracy of manual motor function using machine learning. Results: Amnestic MCI and AD subjects exhibited slower psychomotor speed and AD subjects had weaker dominant hand grip strength than CN subjects. Performance on these measures was related to amyloid β deposition (both) and hippocampal volume (psychomotor speed only). Support vector classification well-discriminated control and AD subjects (area under the curve of 0.73 and 0.77, respectively) but poorly discriminated MCI from controls or AD. Conclusion: Grip strength and spiral tracing appear preserved, while psychomotor speed is affected in amnestic MCI and AD. The association of motor performance with amyloid β deposition and atrophy could indicate that this is due to amyloid deposition in and atrophy of motor brain regions, which generally occurs later in the disease process. The promising discriminatory abilities of manual motor measures for AD emphasize their value alongside other cognitive and motor assessment outcomes in classification and prediction models, as well as potential enrichment of outcome variables in AD clinical trials.

Distinct biological property of tau in tau-first cognitive proteinopathy: Evidence by longitudinal clinical neuroimaging profiles and compared with late-onset Alzheimer disease.

Tau-first cognitive proteinopathy (TCP) denotes a clinical phenotype of Alzheimer disease (AD) showing Florzolotau(18F) positron emission tomography (PET) positivity but a negative amyloid status. We explored the biological property of tau using longitudinal cognitive and neuroimaging data in TCP and compared with late-onset AD (LOAD). We enrolled 56 patients with LOAD, 34 patients with TCP, and 26 cognitive unimpaired controls. All of the participants had historical data of 2 to 4 three-dimensional T1 images and 2 to 6 annual cognitive evaluations over a follow-up period of 7 years. Tau topography was measured using Florzolotau(18F) PET. In the LOAD and TCP groups, we constructed tau or gray matter clusters covarying with the cognitive measurements. We used mediator analysis to explore the regional tau load as predictor, gray matter partitions as mediators, and significant cognitive test scores as outcomes. Longitudinal cognitive decline and cortical thickness degeneration pattern were analyzed using a linear mixed-effects model. The TCP group had longitudinal declines in nonexecutive domains. The deterministic factor predicting the short-term memory score in TCP was the hippocampal volume and not directly via the medial and lateral temporal tau load. These features formed the conceptual differences with LOAD. The biological properties of tau and the longitudinal cognitive-imaging trajectory support the conceptual distinction between TCP and LOAD. TCP represents one specific entity featuring salient short-term memory impairment, declines in nonexecutive domains, a slower gray matter degenerative pattern, and a restricted impact of tau.

Comparison of detailed brain volume measurements in schizophrenia with healthy individuals

Aims: This study aims to provide insights into the preliminary and definitive diagnosis, treatment modalities, and elucidation of the underlying pathophysiological mechanisms of schizophrenia, alongside ongoing research efforts. Methods: This retrospective study examined a cohort of 31 patients (17 male, 14 female) diagnosed with schizophrenia according to the criteria specified in the Diagnostic and Statistical Manual of Mental Disorders (DSM V) at the Psychiatry Clinic of the University Hospital. The healthy control group, comprising 31 individuals (17 male, 14 female), was selected from archived records at the same hospital, with sociodemographic characteristics matching those of the patient group. High-resolution T1-weighted MRI images of the individuals were analyzed using the VolBrain AssemblyNet program. Results: It has been observed that the volumes of various brain structures, including white matter (WM), gray matter (GM), subcortical GM, cortical GM, WM+GM, IC, total cerebrum, right cerebrum, left cerebrum, cerebrum WM, cerebrum GM, are significantly reduced (p<0.05) in patients diagnosed with schizophrenia compared to healthy controls. Additionally, volumes of cerebellar WM, GM, vermis, brainstem, accumbens, hippocampus, thalamus, ventral diencephalon (DC), amygdala, and basal forebrain were found to be decreased in schizophrenia patients compared to healthy controls. Conversely, volumes of the pallidum, caudate, putamen, inferior lateral ventricle, lateral ventricle, third ventricle, fourth ventricle, and CSF were observed to be increased. Conclusion: These findings underscore the widespread nature of neuroanatomical alterations in schizophrenia and highlight the importance of understanding these changes for elucidating the disorder's pathophysiology and developing targeted therapeutic interventions. Further research is warranted to explore the interplay of genetic, developmental, and environmental factors in schizophrenia.

Potential prognostic value of CSF-targeted proteomics across the Alzheimer’s disease continuum

BackgroundCore biomarkers for Alzheimer’s disease (AD), such as Aβ42 and tau, have demonstrated high prognostic accuracy but do not fully capture the complex pathophysiology of AD. In this study, our objective was to identify novel cerebrospinal fluid (CSF) biomarkers using proteomics across the entire AD continuum to predict conversion to AD and explore their involvement in AD pathogenesis.MethodsA cohort of 186 cognitively normal (CN), 127 subjective memory complaint (SMC), 79 early mild cognitive impairment (EMCI), 249 late MCI (LMCI), and 132 AD individuals was analyzed, with a follow-up period of over 3 years for non-AD participants. CSF 65 peptides, as well as hippocampal and entorhinal volumes were analyzed, and cognitive function was evaluated using the 13-item cognitive subscale of the Alzheimer’s Disease Assessment Scale (ADAS-Cog 13). Cox proportional hazards models and mediation analysis were performed to investigate associations and causal relationships.ResultsDuring the follow-up, approximately one-fourth (146/580) of the non-AD participants progressed to AD. After adjusting for baseline diagnosis (CN to LMCI) and other variables, multivariable Cox regression analysis identified three peptides (VAELEDEK, VSFELFADK, and VVSSIEQK) as significant predictors of conversion to AD. Incorporating these three peptides into the initial model significantly improved the C-statistic from 0.82 to 0.85 for predicting AD conversion, surpassing the predictive ability of Aβ42 and P-tau. Moreover, hippocampal and entorhinal volumes mediated 30.3–53.8% of the association between the three peptides and ADAS-Cog 13 scores.ConclusionsThese findings underscore the potential of these three peptides as robust prognostic biomarker candidates for AD conversion across the entire AD continuum, with a mechanism involving the mediation of hippocampal and entorhinal volumes.

Hippocampal volumes in UK Biobank are associated with APOE only in older adults.

The hippocampus atrophies with age and is implicated in neurodegenerative disorders including Alzheimer's disease (AD). We examined the interplay between age and APOE genotype on total hippocampal volume. Utilizing neuroimaging data from 37,463 UK Biobank participants, we applied linear regression to quantify the association of age and APOE with hippocampal volume and identified the age when volumes of ε2/ε3, ε3/ε4, and ε4/ε4 carriers significantly deviated from ε3/ε3 using generalized additive modeling. Total hippocampal volume declined with age, with significant differences by APOE genotype emerging after age 60. ε3/ε4 and ε4/ε4 carriers displayed reduced volumes from ages 69 and 61, respectively, while ε2/ε3 showed delayed decline starting at age 76. The association of APOE and hippocampal volume is age-dependent, with differences in volumes of ε4/ε4 carriers detected as early as age 61. This work underscores the importance of APOE genotype in determining when to begin screening for AD.

Estimating individual trajectories of structural and cognitive decline in mild cognitive impairment for early prediction of progression to dementia of the Alzheimer’s type

Only a third of individuals with mild cognitive impairment (MCI) progress to dementia of the Alzheimer’s type (DAT). Identifying biomarkers that distinguish individuals with MCI who will progress to DAT (MCI-Converters) from those who will not (MCI-Non-Converters) remains a key challenge in the field. In our study, we evaluate whether the individual rates of loss of volumes of the Hippocampus and entorhinal cortex (EC) with age in the MCI stage can predict progression to DAT. Using data from 758 MCI patients in the Alzheimer’s Disease Neuroimaging Database, we employ Linear Mixed Effects (LME) models to estimate individual trajectories of regional brain volume loss over 12 years on average. Our approach involves three key analyses: (1) mapping age-related volume loss trajectories in MCI-Converters and Non-Converters, (2) using logistic regression to predict progression to DAT based on individual rates of hippocampal and EC volume loss, and (3) examining the relationship between individual estimates of these volumetric changes and cognitive decline across different cognitive functions—episodic memory, visuospatial processing, and executive function. We find that the loss of Hippocampal volume is significantly more rapid in MCI-Converters than Non-Converters, but find no such difference in EC volumes. We also find that the rate of hippocampal volume loss in the MCI stage is a significant predictor of conversion to DAT, while the rate of volume loss in the EC and other additional regions is not. Finally, individual estimates of rates of regional volume loss in both the Hippocampus and EC, and other additional regions, correlate strongly with individual rates of cognitive decline. Across all analyses, we find significant individual variation in the initial volumes and the rates of changes in volume with age in individuals with MCI. This study highlights the importance of personalized approaches in predicting AD progression, offering insights for future research and intervention strategies.

Associations between renal function, hippocampal volume, and cognitive impairment in 544 outpatients.

Cognitive impairment and brain atrophy are common in chronic kidney disease patients. It remains unclear whether differences in renal function, even within normal levels, influence hippocampal volume (HCV) and cognition. We aimed to investigate the association between estimated glomerular filtration rate (eGFR), HCV and cognition in outpatients. This single-center retrospective study enrolled 544 nonrenal outpatients from our hospital. All participants underwent renal function assessment and 3.0 T magnetic resonance imaging (MRI) in the same year. HCV was also measured, and cognitive assessments were obtained. The correlations between eGFR, HCV, and cognitive function were analyzed. Logistic regression analysis was performed to identify the risk factors for hippocampal atrophy and cognitive impairment. Receiver-operator curves (ROCs) were performed to find the cut-off value of HCV that predicts cognitive impairment. The mean age of all participants was 66.5 ± 10.9 years. The mean eGFR of all participants was 88.5 ± 15.1 mL/min/1.73 m2. eGFR was positively correlated with HCV and with Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Univariate and multivariate logistic regression analysis showed Age ≥ 65 years, eGFR < 75 mL/min/1.73 m2, Glucose ≥6.1 mmol/L and combined cerebral microvascular diseases were independent risk factors for hippocampal atrophy and Age ≥ 65 years, left hippocampal volume (LHCV) <2,654 mm3 were independent risk factors for cognitive impairment in outpatients. Although initial unadjusted logistic regression analysis indicated that a lower eGFR (eGFR < 75 mL/min/1.73 m2) was associated with poorer cognitive function, this association was lost after adjusting for confounding variables. ROC curve analysis demonstrated that LHCV <2,654 mm3 had the highest AUROC [(0.842, 95% CI: 0.808-0.871)], indicating that LHCV had a credible prognostic value with a high sensitivity and specificity for predicting cognitive impairment compared with age in outpatients. Higher eGFR was associated with higher HCV and better cognitive function. eGFR < 75 mL/min/1.73 m2 was an independent risk factor for hippocampal atrophy after adjusting for age. It is suggested that even eGFR < 75 mL/min/1.73 m2, lower eGFR may still be associated with hippocampal atrophy, which is further associated with cognitive impairment. LHCV was a favorable prognostic marker for predicting cognitive impairment rather than age.

Hippocampal volume and affect in response to fluctuating estrogens in menstrual cycle irregularity: a longitudinal single-subject study

Irregular menstrual cycles, affecting approximately 30% of women in their reproductive years, are often overlooked in research, limiting our insights into the broader spectrum of hormonal interactions. Understanding the relationship between endogenous hormone fluctuations and brain function across the menstrual cycle, particularly beyond regular menstrual cycles, is essential for comprehending mental disorders prevalent in women. To this aim, a healthy female with an irregular menstrual cycle underwent dense sampling for 5 consecutive weeks, primarily covering the follicular phase and ovulation. Blood draws provided measurements of estradiol, estrone, and progesterone. T1-weighted MRI scans assessed bilateral hippocampal volumes. Positive and negative affect were collected at each session. Statistical analyses included cubic regression curves, Spearman correlations, and mediation regression models to explore hormonal associations with hippocampal morphology and affect. Significant fluctuations in hormonal concentrations, hippocampal volume, and affect were observed across the 25 testing days. Estradiol and estrone significantly correlated with hippocampal volume, while progesterone showed no significant association. Increasing concentrations of estrogens were linked to decreasing positive affect, mediated by hippocampal volume fluctuations. Increasing concentrations of estrogens were further associated with increasing negative affect, however, independently of hippocampal changes. Our findings suggest potential roles of estrogens in affect regulation and brain function in a participant with an irregular menstrual cycle. This research serves as a blueprint for future investigations into the complex interplay between sex hormones and structural brain dynamics beyond regular menstrual cycles and establishes a fundamental framework for the advancement of sex-specific precision medicine.

Latent diffusion model-based MRI superresolution enhances mild cognitive impairment prognostication and Alzheimer's disease classification

IntroductionTimely diagnosis and prognostication of Alzheimer's disease (AD) and mild cognitive impairment (MCI) are pivotal for effective intervention. Artificial intelligence (AI) in neuroradiology may aid in such appropriate diagnosis and prognostication. This study aimed to evaluate the potential of novel diffusion model-based AI for enhancing AD and MCI diagnosis through superresolution (SR) of brain magnetic resonance (MR) images. Methods1.5T brain MR scans of patients with AD or MCI and healthy controls (NC) from Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) were superresolved to 3T using a novel diffusion model-based generative AI (d3T*) and a convolutional neural network-based model (c3T*). Comparisons of image quality to actual 1.5T and 3T MRI were conducted based on signal-to-noise ratio (SNR), naturalness image quality evaluator (NIQE), and Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE). Voxel-based volumetric analysis was then conducted to study whether 3T* images offered more accurate volumetry than 1.5T images. Binary and multiclass classifications of AD, MCI, and NC were conducted to evaluate whether 3T* images offered superior AD classification performance compared to actual 1.5T MRI. Moreover, CNN-based classifiers were used to predict conversion of MCI to AD, to evaluate the prognostication performance of 3T* images. The classification performances were evaluated using accuracy, sensitivity, specificity, F1 score, Matthews correlation coefficient (MCC), and area under the receiver-operating curves (AUROC). ResultsAnalysis of variance (ANOVA) detected significant differences in image quality among the 1.5T, c3T*, d3T*, and 3T groups across all metrics. Both c3T* and d3T* showed superior image quality compared to 1.5T MRI in NIQE and BRISQUE with statistical significance. While the hippocampal volumes measured in 3T* and 3T images were not significantly different, the hippocampal volume measured in 1.5T images showed significant difference. 3T*-based AD classifications showed superior performance across all performance metrics compared to 1.5T-based AD classification. Classification performance between d3T* and actual 3T was not significantly different. 3T* images offered superior accuracy in predicting the conversion of MCI to AD than 1.5T images did. ConclusionsThe diffusion model-based MRI SR enhances the resolution of brain MR images, significantly improving diagnostic and prognostic accuracy for AD and MCI. Superresolved 3T* images closely matched actual 3T MRIs in quality and volumetric accuracy, and notably improved the prediction performance of conversion from MCI to AD.

Evolutionary lability of food caching behaviour in mammals.

Food hoarding provides animals access to resources during periods of scarcity. Studies on mammalian caching indicate associations with brain size, seasonality and diet but are biased to a subset of rodents. Whether the behaviour is generalizable at other taxonomic scales and/or is influenced by other ecological factors is less understood. Population density may influence food caching due to food competition or pilferage, but this remains untested in a comparative framework. Using phylogenetic analyses, we assessed the role of morphology (body and brain size), climate, diet breadth and population density on food caching behaviour evolution at multiple taxonomic scales. We also used a long-term dataset on caching behaviour of red squirrels (Tamiasciurus fremonti) to test key factors (climate and population density) on hoarding intensity. Consistent with previous smaller scale studies, we found the mammalian ancestral state for food caching was larderhoarding, and scatterhoarding was derived. Caching strategy was strongly associated with brain size, population density and climate. Mammals with larger brains and hippocampal volumes were more likely to scatterhoard, and species living at higher population densities and in colder climates were more likely to larderhoard. Finer-scale analyses within families, sub-families and tribes indicated that the behaviour is evolutionary labile. Brain size in family Sciuridae and tribe Marmotini was larger in scatterhoarders, but not in other tribes. Scatterhoarding in tribe Marmotini was more likely in species with lower population densities while scatterhoarding in tribe Sciurini was associated with warmer climates. Red squirrel larderhoarding intensity was positively related to population density but not climate, implicating food competition or pilferage as an important mechanism mediating caching behaviour. Our results are consistent with previous smaller-scale studies on food caching and indicate the evolutionary patterns of mammalian food caching are broadly generalizable. Given the lability of caching behaviour as evidenced by the variability of our results at finer phylogenetic scales, comparative analyses must consider taxonomic scale. Applying our results to conservation could prove useful as changes in population density or climate may select for different food caching strategies and thus can inform management of threatened and endangered species and their habitats.

Prenatal Maternal Psychological Distress During the COVID-19 Pandemic and Newborn Brain Development

Elevated maternal psychological distress during pregnancy is associated with altered fetal brain development. During the COVID-19 pandemic, prenatal maternal psychological distress more than doubled. To examine the association of the pandemic and rising maternal psychological distress with brain growth in newborns using quantitative 3-dimensional volumetric magnetic resonance imaging (MRI). This prospective cross-sectional study recruited mother-infant dyads at Children's National Hospital, Washington, DC, during the COVID-19 pandemic (June 1, 2020, to June 30, 2022) into a longitudinal infant brain development study and compared them with an existing normative healthy cohort (recruited March 1, 2014, to December 31, 2019). Exclusion criteria included multiple gestation pregnancy, known or suspected congenital infection, documented chromosomal abnormalities, or any maternal contraindication to MRI, as well as prenatal COVID-19 exposure. Infants with structural brain abnormalities or a postnatal confirmation of a genetic syndrome were excluded. Psychological distress during COVID-19 pandemic. Prenatal maternal mental health was evaluated using the Spielberger State-Trait Anxiety Inventory and the Perceived Stress Scale. Neonates underwent nonsedated brain MRI. An ordinary least squares linear regression model was used to measure the differences in regional brain volumes of neonates born before vs during the pandemic with and without exposure to elevated prenatal maternal psychological distress after adjustment for neonatal sex and gestational age at MRI and maternal age and educational level. A total of 159 mother-infant dyads were included in the analysis: 103 before and 56 during the pandemic (median gestational age of infants, 39.6 [IQR, 38.4-40.4] weeks; median maternal age, 34.5 [IQR, 31.0-37.0] years). Eighty-three infants (52.2%) were female. Among the mothers, 130 (81.8%) had a college degree and 87 (54.7%) had a graduate degree. Forty-four mothers (27.7%) identified as Asian, Hispanic, or multiracial; 27 (17.0%), as Black; and 88 (55.3%), as White. Scores on anxiety and stress measures were significantly increased in the pandemic cohort. Infants of mothers with elevated maternal distress showed median reductions in white matter (-0.36 [95% CI, -0.61 to -0.11] cm3; Q < .001), right hippocampal (-0.35 [95% CI, -0.65 to -0.06] cm3; Q = .04), and left amygdala (-0.49 [95% CI, -0.84 to -0.13] cm3; Q = .03) volumes compared with infants of mothers with low distress levels. After adjusting for the cohort effect of the pandemic, elevated trait anxiety remained significantly associated with decreased left amygdalar volumes (-0.71 [95% CI, -1.12 to -0.29]; Q < .001). In this cross-sectional study of maternal-infant dyads prior to and during the COVID-19 pandemic, regional neonatal brain volumes were associated with elevated maternal psychological distress.

Hippocampus and amygdala volumes are reduced in patients with schizoaffective disorder

We aimed to examine the hippocampus and amygdala volumes in patients with schizoaffective disorder with the notion that schizoaffective disorder has strong resemblance of clinical presentation with schizophrenia and bipolar disorder and that there have been studies on regions of interest volumes in patients with schizophrenia and bipolar disorder but not in patients with schizoaffective disorder. Eighteen patients with schizoaffective disorder and nineteen healthy controls were included into the study. Hippocampus and amygdala volumes were examined by using the MRI. Both hippocampus and amygdala volumes were statistically significantly reduced in patients with schizoaffective disorder compared to those of the healthy control comparisons (p<0.001 for the hippocampus and p<0.001 for the amygdala). In summary, our findings of the present study suggest that patients with schizoaffective disorder seem to have smaller volumes of the hippocampus and amygdala regions and that our results were in accordance with those obtained both in patients with schizophrenia and bipolar disorder, considering that schizoaffective disorder might have neuroanatomic similarities with both schizophrenia and bipolar disorder. Beacuse of some limitations aforementioned especially age, it is required to replicate our present results in this patient group.

Investigating the volume of hippocampus and corpus callosum in Iranian multiple sclerosis patients using magnetic resonance imaging: a retrospective study

Multiple Sclerosis (MS) is one of the most common forms of the acquired autoimmune demyelinating disorder affecting the brain. The neurological symptoms of MS are often presented in a relapsing-remitting manner. This study aims to investigate volume changes in the hippocampus and Corpus Callosum (CC). A cross-sectional study was conducted on 200 MS patients, 100 males and 100 females, aged 20-56 years. According to McDonald’s 2017 criteria,100 patients were in the MS group, and 100 were in the control group. This study assessed volume changes in the hippocampus and CC with ITK-SNAP 4.0 software. Our study revealed that the volumes of the right Hippocampus (P&lt;0.0001), left Hippocampus (P&lt;0.05), and corpus callosum (P&lt;0.001), were significantly decreased in MS group compared to control group, regardless of the sex of the patients. Additionally, our results showed that the volume of these three areas has no significant difference with the age of MS patients. This research shows that some brain regions, including the hippocampus and corpus callosum, can be essential landmarks in determining MS disease.

Beyond the hippocampus: Amygdala and memory functioning in older adults

BackgroundMedial temporal lobe atrophy has been linked to decline in neuropsychological measures of explicit memory function. While the hippocampus has long been identified as a critical structure in learning and memory processes, less is known about contributions of the amygdala to these functions. We sought to investigate the relationship between amygdala volume and memory functioning in a clinical sample of older adults with and without cognitive impairment. MethodsA serial clinical sample of older adults that underwent neuropsychological assessment at an outpatient neurology clinic was selected for retrospective chart review. Patients were included in the study if they completed a comprehensive neuropsychological assessment within six months of a structural magnetic resonance imaging scan. Regional brain volumes were quantified using Neuroreader® software. Associations between bilateral hippocampal and amygdala volumes and memory scores, derived from immediate and delayed recall conditions of a verbal story learning task and a visual design reconstruction task, were examined using mixed-effects general linear models, controlling for total intracranial volume, scanner model, age, sex and education. Partial correlation coefficients, adjusted for these covariates, were calculated to estimate the strength of the association between volumes and memory scores. ResultsA total of 68 (39 F, 29 M) participants were included in the analyses, with a mean (SD) adjusted age of 80.1 (6.0) and educational level of 15.9 (2.5) years. Controlling for age, sex, education, and total intracranial volume, greater amygdala volumes were associated with better verbal and visual memory performance, with effect sizes comparable to hippocampal volume. No significant lateralized effects were observed. Partial correlation coefficients ranged from 0.47 to 0.33 (p<.001). ConclusionThese findings contribute to a growing body of knowledge identifying the amygdala as a target for further research in memory functioning. This highlights the importance of considering the broader functioning of the limbic system in which multiple subcortical structures contribute to memory processes and decline in older adults.

A Mendelian randomization study of the entire phenome to explore the causal links between epilepsy.

The causes and triggering factors of epilepsy are still unknown. The results of genome-wide association studies can be utilized for a phenome-wide association study using Mendelian randomization (MR) to identify potential risk factors for epilepsy. This study utilizes two-sample MR analysis to investigate whether 316 phenotypes, including lifestyle, environmental factors, blood biomarker, and more, are causally associated with the occurrence of epilepsy. The primary analysis employed the inverse variance weighted (IVW) model, while complementary MR analysis methods (MR Egger, Wald ratio) were also employed. Sensitivity analyses were also conducted to evaluate heterogeneity and pleiotropy. There was no evidence of a statistically significant causal association between the examined phenotypes and epilepsy following Bonferroni correction (p<1.58 × 10-4) or false discovery rate correction. The results of the MR analysis indicate that the frequency of tiredness or lethargy in the last 2weeks (p=0.042), blood uridine (p=0.003), blood propionylcarnitine (p=0.041), and free cholesterol (p=0.044) are suggestive causal risks for epilepsy. Lifestyle choices, such as sleep duration and alcohol consumption, as well as biomarkers including steroid hormone levels, hippocampal volume, and amygdala volume were not identified as causal factors for developing epilepsy (p>0.05). Our study provides additional insights into the underlying causes of epilepsy, which will serve as evidence for the prevention and control of epilepsy. The associations observed in epidemiological studies may be partially attributed to shared biological factors or lifestyle confounders.

The impact of gut microbial dysbiosis on the atrophy of the hippocampus and abnormal metabolism of N-acetyl aspartate in type 2 diabetic rats

Rationale and objectivesThis study aimed to investigate the effect of intestinal dysbiosis on the hippocampal volume using proton magnetic resonance spectroscopy (1H-MRS) in a type 2 diabetes mellitus (T2DM) rat model. Materials and methodsWe established a T2DM animal model with high-fat diet and streptozotocin (HFD/STZ) administration to Sprague-Dawley rats. Short-term ceftriaxone sodium administration was used to establish a T2DM intestinal dysbiosis (T2DM-ID) model. After establishing the model, fecal microbiota were detected using 16S rRNA sequencing. The models were then subjected to magnetic resonance imaging (MRI). Associations between MRI findings and fecal microbiota were evaluated. ResultsMagnetic resonance imaging (MRI) showed that the bilateral hippocampal voxel value and N-acetylaspartate (NAA) level were lower in the experimental group than in the normal control (NC) group (p < 0.05) and that NAA/creatine in the left hippocampus was lower in the T2DM-ID group than in the NC group (p < 0.05). α and β diversities differed significantly among the three groups (p < 0.05). In the T2DM and T2DM-ID groups, the abundance of bacteria in the phylum Proteobacteria increased significantly, whereas that of bacteria in the phylum Firmicutes decreased. The relative abundance of Actinobacteria was significantly increased in the T2DM-ID group. The Chao1 index (r = 0.33, p < 0.05) and relative abundance of Firmicutes (r = 0.48, p < 0.05) were positively correlated with the left hippocampal voxel, while the relative abundance of Proteobacteria was negatively correlated with the left hippocampal voxel (r = −0.44, p < 0.05). NAA levels, bilateral hippocampal voxels, and the relative abundance of Lactobacillus, Clostridia_UCG_014, and other genera were correlated positively (r = 0.34–0.70, p < 0.05). NAA levels and the relative abundances of Blautia and Enterococcus were correlated negatively (r = −0.32−0.44, p < 0.05). ConclusionThe T2DM-ID rat model showed hippocampal volume atrophy and decreased levels of neuronal markers (such as NAA). The abnormal content of specific gut microorganisms may be a key biomarker of T2DM-associated brain damage.

1-Methyltryptophan treatment ameliorates high-fat diet-induced depression in mice through reversing changes in perineuronal nets

Depression and obesity are prevalent disorders with significant public health implications. In this study, we used a high-fat diet (HFD)-induced obese mouse model to investigate the mechanism underlying HFD-induced depression-like behaviors. HFD-induced obese mice exhibited depression-like behaviors and a reduction in hippocampus volume, which were reversed by treatment with an indoleamine 2,3-dioxygenase (IDO) inhibitor 1-methyltryptophan (1-MT). Interestingly, no changes in IDO levels were observed post-1-MT treatment, suggesting that other mechanisms may be involved in the anti-depressive effect of 1-MT. We further conducted RNA sequencing analysis to clarify the potential underlying mechanism of the anti-depressive effect of 1-MT in HFD-induced depressive mice and found a significant enrichment of shared differential genes in the extracellular matrix (ECM) organization pathway between the 1-MT-treated and untreated HFD-induced depressive mice. Therefore, we hypothesized that changes in ECM play a crucial role in the anti-depressive effect of 1-MT. To this end, we investigated perineuronal nets (PNNs), which are ECM assemblies that preferentially ensheath parvalbumin (PV)-positive interneurons and are involved in many abnormalities. We found that HFD is associated with excessive accumulation of PV-positive neurons and upregulation of PNNs, affecting synaptic transmission in PV-positive neurons and leading to glutamate-gamma-aminobutyric acid imbalances in the hippocampus. The 1-MT effectively reversed these changes, highlighting a PNN-related mechanism by which 1-MT exerts its anti-depressive effect.

PET/MRI multimodality imaging to evaluate changes in glymphatic system function and biomarkers of Alzheimer’s disease

The glymphatic system is considered to play a pivotal role in the clearance of disease-causing proteins in neurodegenerative diseases. This study employed MR diffusion tensor imaging (DTI) to evaluate glymphatic system function and its correlation with brain amyloid accumulation levels measured using [11C]Pittsburgh compound-B (PiB) PET/MRI. Fifty-six patients with mild cognitive impairment and early Alzheimer’s disease (AD: 70 ± 11 y) underwent [11C]PiB PET/MRI to assess amyloid deposition and were compared with 27 age-matched cognitively normal volunteers (CN: 69 ± 10y). All participants were evaluated for cognitive function using the Mini Mental State Examination (MMSE) before [11C]PiB PET/MRI. DTI images were acquired during the PET/MRI scan with several other MR sequences. The DTI analysis along the perivascular space index (DTI-ALPS index) was calculated to estimate the functional activity of the glymphatic system. Centiloid scale was applied to quantify amyloid deposition levels from [11C]PiB PET images. All patients in the AD group showed positive [11C]PiB accumulation, whereas all CN participants were negative. ALPS-index for all subjects linearly correlated with PiB centiloid, MMSE scores, and hippocampal volume. The correlation between the ALPS-index and PiB accumulation was more pronounced than with any other biomarkers. These findings suggest that glymphatic system dysfunction is a significant factor in the early stages of Alzheimer’s disease.

Continuous Associations between Remote Self-Administered Cognitive Measures and Imaging Biomarkers of Alzheimer’s Disease

BackgroundEasily accessible and self-administered cognitive assessments that can aid early detection for Alzheimer’s disease (AD) dementia risk are critical for timely intervention.Objectives/DesignThis cross-sectional study investigated continuous associations between Mayo Test Drive (MTD)–a remote, self-administered, multi-device compatible, web-based cognitive assessment–and AD-related imaging biomarkers.Participants/Setting684 adults from the Mayo Clinic Study of Aging and Mayo Clinic Alzheimer’s Disease Research Center participated (age=70.4±11.2, 49.7% female). Participants were predominantly cognitively unimpaired (CU; 94.0%).MeasurementsParticipants completed (1) brain amyloid and tau PET scans and MRI scans for hippocampal volume (HV) and white matter hyperintensities (WMH); (2) MTD remotely, consisting of the Stricker Learning Span and Symbols Test which combine into an MTD composite; and (3) in-person neuropsychological assessment including measures to obtain Mayo Preclinical Alzheimer’s disease Cognitive Composite (Mayo-PACC) and Global-z. Multiple regressions adjusted for age, sex, and education queried associations between imaging biomarkers and scores from remote and in-person cognitive measures.ResultsLower performances on MTD were associated with greater amyloid, entorhinal tau, and global tau PET burden, lower HV, and higher WMH. Mayo-PACC and Global-z were associated with all imaging biomarkers except global tau PET burden. MCI/Dementia participants showed lower performance on all MTD measures compared to CU with large effect sizes (Hedge’s g’s=1.65–2.02), with similar findings for CU versus MCI only (Hedge’s g’s=1.46–1.83).ConclusionMTD is associated with continuous measures of AD-related imaging biomarkers, demonstrating ability to detect subtle cognitive change using a brief, remote assessment in predominantly CU individuals and criterion validity for MTD.

TDP-43 Is Associated with Subiculum and Cornu Ammonis 1 Hippocampal Subfield Atrophy in Primary Age-Related Tauopathy.

TAR DNA binding protein 43 (TDP-43) has been shown to be associated with whole hippocampal atrophy in primary age-related tauopathy (PART). It is currently unknown which subregions of the hippocampus are contributing to TDP-43 associated whole hippocampal atrophy in PART. To identify which specific hippocampal subfield regions are contributing to TDP-43-associated whole hippocampal atrophy in PART. A total of 115 autopsied cases from the Mayo Clinic Alzheimer Disease Research Center, Neurodegenerative Research Group, and the Mayo Clinic Study of Aging were analyzed. All cases underwent antemortem brain volumetric MRI, neuropathological assessment of the distribution of Aβ (Thal phase), and neurofibrillary tangle (Braak stage) to diagnose PART, as well as assessment of TDP-43 presence/absence in the amygdala, hippocampus and beyond. Hippocampal subfield segmentation was performed using FreeSurfer version 7.4.1. Statistical analyses using logistic regression were performed to assess for associations between TDP-43 and hippocampal subfield volumes, accounting for potential confounders. TDP-43 positive patients (n = 37, 32%), of which 15/15 were type-α, had significantly smaller whole hippocampal volumes, and smaller volumes of the body and tail of the hippocampus compared to TDP-43 negative patients. Subfield analyses revealed an association between TDP-43 and the molecular layer of hippocampal body and the body of cornu ammonis 1 (CA1), subiculum, and presubiculum regions. There was no association between TDP-43 stage and subfield volumes. Whole hippocampal volume loss linked to TDP-43 in PART is mainly due to volume loss occurring in the molecular layer, CA1, subiculum and presubiculum of the hippocampal body.