Brain Aging Research Articles

Pathologic Substrates of Structural Brain Network Resilience and Topology in Parkinson Disease Decedents.

In Parkinson disease (PD), α-synuclein spreading through connected brain regions leads to neuronal loss and brain network disruptions. With diffusion-weighted imaging (DWI), it is possible to capture conventional measures of brain network organization and more advanced measures of brain network resilience. We aimed to investigate which neuropathologic processes contribute to regional network topologic changes and brain network resilience in PD. Using a combined postmortem MRI and histopathology approach, PD and control brain donors with available postmortem in situ 3D T1-weighted MRI, DWI, and brain tissue were selected from the Netherlands Brain Bank and Normal Aging Brain Collection Amsterdam. Probabilistic tractography was performed, and conventional network topologic measures of regional eigenvector centrality and clustering coefficient, and brain network resilience (change in global efficiency upon regional node failure) were calculated. PSer129 α-synuclein, phosphorylated-tau, β-amyloid, neurofilament light-chain immunoreactivity, and synaptophysin density were quantified in 8 cortical regions. Group differences and correlations were assessed with rank-based nonparametric tests, with age, sex, and postmortem delay as covariates. Nineteen clinically defined and pathology-confirmed PD (7 F/12 M, 81 ± 7 years) and 15 control (8 F/7 M, 73 ± 9 years) donors were included. With regional conventional measures, we found lower eigenvector centrality only in the parahippocampal gyrus in PD (d = -1.08, 95% CI 0.003-0.010, p = 0.021), which did not associate with underlying pathology. No differences were found in regional clustering coefficient. With the more advanced measure of brain network resilience, we found that the PD brain network was less resilient to node failure of the dorsal anterior insula compared with the control brain network (d = -1.00, 95% CI 0.0012-0.0015, p = 0.018). This change was not directly driven by neuropathologic processes within the dorsal anterior insula or in connected regions but was associated with higher Braak α-synuclein staging (rs = -0.40, p = 0.036). Although our cohort might suffer from selection bias, our results highlight that regional network disturbances are more complex to interpret than previously believed. Regional neuropathologic processes did not drive regional topologic changes, but a global increase in α-synuclein pathology had a widespread effect on brain network reorganization in PD.

Decoding MRI-informed brain age using mutual information

ObjectiveWe aimed to develop a standardized method to investigate the relationship between estimated brain age and regional morphometric features, meeting the criteria for simplicity, generalization, and intuitive interpretability.MethodsWe utilized T1-weighted magnetic resonance imaging (MRI) data from the Cambridge Centre for Ageing and Neuroscience project (N = 609) and employed a support vector regression method to train a brain age model. The pre-trained brain age model was applied to the dataset of the brain development project (N = 547). Kraskov (KSG) estimator was used to compute the mutual information (MI) value between brain age and regional morphometric features, including gray matter volume (GMV), white matter volume (WMV), cerebrospinal fluid (CSF) volume, and cortical thickness (CT).ResultsAmong four types of brain features, GMV had the highest MI value (8.71), peaking in the pre-central gyrus (0.69). CSF volume was ranked second (7.76), with the highest MI value in the cingulate (0.87). CT was ranked third (6.22), with the highest MI value in superior temporal gyrus (0.53). WMV had the lowest MI value (4.59), with the insula showing the highest MI value (0.53). For brain parenchyma, the volume of the superior frontal gyrus exhibited the highest MI value (0.80).ConclusionThis is the first demonstration that MI value between estimated brain age and morphometric features may serve as a benchmark for assessing the regional contributions to estimated brain age. Our findings highlighted that both GMV and CSF are the key features that determined the estimated brain age, which may add value to existing computational models of brain age.Critical relevance statementMutual information (MI) analysis reveals gray matter volume (GMV) and cerebrospinal fluid (CSF) volume as pivotal in computing individuals’ brain age.Key PointsMutual information (MI) interprets estimated brain age with morphometric features.Gray matter volume in the pre-central gyrus has the highest MI value for estimated brain age.Cerebrospinal fluid volume in the cingulate has the highest MI value.Regarding brain parenchymal volume, the superior frontal gyrus has the highest MI value.The value of mutual information underscores the key brain regions related to brain age.Graphical

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations.

Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.

Using Dual-Coil TMS-EEG to Probe Bilateral Brain Mechanisms in Healthy Aging and Mild Cognitive Impairment.

A widespread observation in the cognitive neuroscience of aging is that older adults show a more bilateral pattern of task-related brain activation. These observations are based on inherently correlational approaches. The current study represents a targeted assessment of the role of bilaterality using repetitive transcranial magnetic stimulation (rTMS). We used a novel bilateral TMS-stimulation paradigm, applied to a group of healthy older adults (hOA) and older adults with mild cognitive impairment (MCI), with two aims: First, to elucidate the neurophysiological effects of bilateral neuromodulation, and second to provide insight into the neurophysiological basis of bilateral brain interactions. Electroencephalography (EEG) was recorded while participants received six forms of transcranial magnetic stimulation (TMS): unilateral and bilateral rTMS trains at an alpha (8 Hz) and beta (18 Hz) frequency, as well as two sham conditions (unilateral, bilateral) mimicking the sounds of TMS. First, time-frequency analyses of oscillatory power induced by TMS revealed that unilateral beta rTMS elicited rhythmic entrainment of cortical oscillations at the same beta-band frequency. Second, both bilateral alpha and bilateral beta stimulation induced a widespread reduction of alpha power. Lastly, healthy older adults showed greater TMS-related reductions in alpha power in response to bilateral rTMS compared to the MCI cohort. Overall, these results demonstrate frequency-specific responses to bilateral rTMS in the aging brain, and provide support for inhibitory models of hemispheric interaction across multiple frequency bands.

Cell cycle re-entry in the aging Drosophila brain.

The brain is an organ comprised mostly of long-lived, quiescent cells that perform vital functions throughout an animal's life. Due to the brain's limited regenerative ability, these long-lived cells must engage unique mechanisms to cope with accumulated damage over time. We have shown that a subset of differentiated neuronal and glial cells in the fruit fly brain become polyploid during adulthood. Cell cycle re-entry in the brain has previously been associated with neurodegeneration, but there may be a more complex relationship between polyploidy and cell fitness in the brain. Here, we examine how known lifespan modifiers influence the accumulation of polyploidy in the aging fly brain. Flies aged at a low temperature, or with a low protein diet, accumulate polyploid cells in the brain more slowly than expected if this phenotype were solely regulated by lifespan mechanisms. Despite the slower accumulation of polyploid cells, animals under conditions that extend lifespan eventually reach similar levels of polyploidy in the brain as controls. Our work suggests known lifespan modifiers can influence the timing of cell cycle re-entry in the adult brain, indicating there is a flexible window of cell cycle plasticity in the aging brain.

Icariin targets p53 to protect against ceramide-induced neuronal senescence: Implication in Alzheimer's disease

BackgroundAlzheimer's disease (AD) is a leading cause of dementia. The aging brain is particularly vulnerable to various stressors, including increased levels of ceramide. However, the role of ceramide in neuronal cell senescence and AD progression and whether icariin, a natural flavonoid glucoside, could reverse neuronal senescence remain inadequately understood. AimIn this study, we explore the role of ceramide in neuronal senescence and AD, and whether icariin can counteract these effects. MethodsWe pretreated HT-22 cells with icariin and then induced senescence with ceramide. Various assays were employed to assess cell senescence, such as reactive oxygen species (ROS) production, cell cycle progression, β-galactosidase staining, and expression of senescence-associated proteins. In vivo studies utilized APP/PS1 mice and C57BL/6J mice injected with ceramide to evaluate behavioral changes, histopathological alterations, and senescence-associated protein expression. Transcriptomics, molecular docking, molecular dynamics simulations, and cellular thermal shift assays were employed to verify the interaction between icariin and P53. The specificity of icariin targeting of P53 was further confirmed through rescue experiments utilizing the P53 activator Navtemadlin. ResultsOur data demonstrated that ceramide could induce neuronal senescence and AD-related pathologies, which were reversed by icariin. Moreover, molecular studies revealed that icariin directly targeted P53, and its neuroprotective effects were attenuated by P53 activation, providing evidence for the role of P53 in icariin-mediated neuroprotection. ConclusionIcariin demonstrates a protective effect against ceramide-induced neuronal senescence by inhibiting the P53 pathway. This identifies a novel mechanism of action for icariin, offering a novel therapeutic approach for AD and other age-related neurodegenerative diseases.

Comparative analysis of brain age prediction using structural and diffusion MRIs in neonates

Using machine learning techniques to predict brain age from multimodal data has become a crucial biomarker for assessing brain development. Among various types of brain imaging data, structural magnetic resonance imaging (sMRI) and diffusion magnetic resonance imaging (dMRI) are the most commonly used modalities. sMRI focuses on depicting macrostructural features of the brain, while dMRI reveals the orientation of major white matter fibers and changes in tissue microstructure. However, their differential capabilities in reflecting newborn age and clinical implications have not been systematically studied. This study aims to explore the impact of sMRI and dMRI on brain age prediction. Comparing predictions based on T2-weighted(T2w) and fractional anisotropy (FA) images, we found their mean absolute errors (MAE) in predicting infant age to be similar. Exploratory analysis revealed for T2w images, areas such as the cerebral cortex and ventricles contribute most significantly to age prediction, whereas FA images highlight the cerebral cortex and regions of the main white matter tracts. Despite both modalities focusing on the cerebral cortex, they exhibit significant region-wise differences, reflecting developmental disparities in macro- and microstructural aspects of the cortex. Additionally, we examined the effects of prematurity, gender, and hemispherical asymmetry of the brain on age prediction for both modalities. Results showed significant differences (p<0.05) in age prediction biases based on FA images across gender and hemispherical asymmetry, whereas no significant differences were observed with T2w images. This study underscores the differences between T2w and FA images in predicting infant brain age, offering new perspectives for studying infant brain development and aiding more effective assessment and tracking of infant development.

T Cells Trafficking into the Brain in Aging and Alzheimer's Disease.

The meninges, choroid plexus (CP) and blood-brain barrier (BBB) are recognized as important gateways for peripheral immune cell trafficking into the central nervous system (CNS). Accumulation of peripheral immune cells in brain parenchyma can be observed during aging and Alzheimer's disease (AD). However, the mechanisms by which peripheral immune cells enter the CNS through these three pathways and how they interact with resident cells within the CNS to cause brain injury are not fully understood. In this paper, we review recent research on T cells recruitment in the brain during aging and AD. This review focuses on the possible pathways through which T cells infiltrate the brain, the evidence that T cells are recruited to the brain, and how infiltrating T cells interact with the resident cells in the CNS during aging and AD. Unraveling these issues will contribute to a better understanding of the mechanisms of aging and AD from the perspective of immunity, and hopefully develop new therapeutic strategies for brain aging and AD.

Cognitive outcomes in late-onset versus adult-onset Multiple Sclerosis

IntroductionRecent studies show that cognitive impairment is more prevalent in older patients with Multiple Sclerosis (MS). However, whether this is the result of several years of a chronic disease or specific age-related changes is still unclear. Therefore, we aim to assess the outcomes in both classic and social cognition in late-onset MS (LOMS) and compare them to adult-onset MS (AOMS) when accounting for age and disease duration. MethodsIn this cross-sectional study, a group of 27 LOMS patients (age of disease onset >50 years) was compared with patients with AOMS (age of disease onset between 18 and 50 years). Patients with AOMS were grouped based on age (AOAMS, n = 27) and on disease duration (AODMS, n = 27) in order that these variables are matched with LOMS. Their cognitive performance was evaluated using the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) and the Revised “Reading the Mind in the Eyes” Test (RMET). Clinical and demographic variables were collected and analysed. ResultsIn general, both classic and social cognitive performance was inferior in the LOMS group when accounting for age and disease duration. We found a statistically significant negative correlation between age of disease onset and performance in all cognitive domains except for verbal memory. The presence of at least one vascular risk factor (VRF) was associated with slower information-processing speed (SDMT) (p = 0.006) and poorer RMET performance (p = 0.020). DiscussionA later age of MS is associated with worse cognitive functioning possibly due to the loss of neuroplasticity in an already aged brain. ConclusionPatients with LOMS have worse cognitive outcomes than AOMS in both classic and social domains, especially when associated with the presence of VRF. Hence, health care providers and patients should not undervalue the importance of cognitive stimulating activities, management of VFR and socialization in this specific group of patients.

Predicting brain atrophy and cognitive aging trajectories with baseline subjective cognitive concerns in cognitively normal older adults

Subjective cognitive concerns (SCC) are common even in cognitively normal older adults who lack objectively-detectable deficits on standard neuropsychological evaluation. The clinical relevance of these concerns, particularly considering the nature of concerns (e.g., memory versus non-memory), remains unclear. Thus, we examined whether baseline memory and non-memory SCC relate to longitudinal change in brain volume and neuropsychological test performance in 476 functionally-intact, objectively unimpaired older adults (Mage = 72y, 56 % female, follow-up time = 1 – 9 years). Mixed-effects models revealed that both higher baseline memory and non-memory SCC predicted greater atrophy in total gray matter and dorsolateral prefrontal cortex atrophy over time, while only memory SCC predicted steeper medial temporal lobe atrophy. Regarding neuropsychological performance, higher non-memory SCC predicted decline in processing speed performance, while memory SCC did not predict neuropsychological trajectories. SCC are a risk factor for more adverse brain and cognitive aging trajectories, even in functionally-intact, seemingly cognitively normal older adults.

Aged Brain Metabolomics Study by Metabolic Profiling Analysis of Amino Acids, Organic Acids, and Fatty Acids in Cortex, Cerebellum, Hypothalamus, and Hippocampus of Rats.

Aging is a progressive process characterized by weakness in brain function. Although metabolomics studies on the brain related with aging have been conducted, it is not yet fully understood. A systematic metabolomics study was performed to search for biomarkers and monitor altered metabolism in various brain tissues of the cortex, cerebellum, hypothalamus, and hippocampus of young (8 months old) and old rats (22 months old). Simultaneous profiling analysis of amino acids (AAs), organic acids (OAs), and fatty acids (FAs) in the brain tissues of young and old rats were performed by gas chromatography-tandem mass spectrometry. Under optimal conditions, AA, OA, and FA profiling methods showed good linearity (r ≥0.995) with limit of detection of ≤30 and 73.2 ng and limit of quantification of ≤90.1 and 219.5 ng, respectively. Repeatability varied from 0.4 to 10.4 and 0.8 to 14.8% relative standard deviation and accuracy varied from -11.3 to 10.3 and -12.8 to 14.1% relative error, respectively. In the profiling analysis, total 32, 43, 45, and 30 metabolites were determined in cortex, cerebellum, hypothalamus, and hippocampus, respectively. In statistical analysis, eight AAs (alanine, valine, leucine, isoleucine, threonine, serine, proline, and phenylalanine) in the cortex and four metabolites (alanine, phenylalanine, 3-hydoxypropionic acid, and eicosadienoic acid) in the cerebellum were significantly evaluated (Q-value <0.05, variable importance in projection scores ≥1.0). In all brain tissues, the score plots of orthogonal partial least square discriminant analysis were clearly separated between the young and old groups. Metabolomics results indicate that mechanistic targets of rapamycin complex 1, branched chain-amino acid, and energy metabolism are related to inflammation and mitochondrial dysfunction in the brain during aging. Thus, these results may explain the characteristic metabolism of brain aging.

An estimate of the longitudinal pace of aging from a single brain scan predicts dementia conversion, morbidity, and mortality.

To understand how aging affects functional decline and increases disease risk, it is necessary to develop accurate and reliable measures of how fast a person is aging. Epigenetic clocks measure aging but require DNA methylation data, which many studies lack. Using data from the Dunedin Study, we introduce an accurate and reliable measure for the rate of longitudinal aging derived from cross-sectional brain MRI: the Dunedin Pace of Aging Calculated from NeuroImaging or DunedinPACNI. Exporting this measure to the Alzheimer's Disease Neuroimaging Initiative and UK Biobank neuroimaging datasets revealed that faster DunedinPACNI predicted participants' cognitive impairment, accelerated brain atrophy, and conversion to diagnosed dementia. Underscoring close links between longitudinal aging of the body and brain, faster DunedinPACNI also predicted physical frailty, poor health, future chronic diseases, and mortality in older adults. Furthermore, DunedinPACNI followed the expected socioeconomic health gradient. When compared to brain age gap, an existing MRI aging biomarker, DunedinPACNI was similarly or more strongly related to clinical outcomes. DunedinPACNI is a "next generation" MRI measure that will be made publicly available to the research community to help accelerate aging research and evaluate the effectiveness of dementia prevention and anti-aging strategies.

Mega-analysis of the brain-age gap in substance use disorder: An ENIGMA Addiction working group study.

The brain age gap (BAG), calculated as the difference between a machine learning model-based predicted brain age and chronological age, has been increasingly investigated in psychiatric disorders. Tobacco and alcohol use are associated with increased BAG; however, no studies have compared global and regional BAG across substances other than alcohol and tobacco. This study aimed to compare global and regional estimates of brain age in individuals with substance use disorders and healthy controls. This was a cross-sectional study. This is an Enhancing Neuro Imaging through Meta-Analysis Consortium (ENIGMA) Addiction Working Group study including data from 38 global sites. This study included 2606 participants, of whom 1725 were cases with a substance use disorder and 881 healthy controls. This study used the Kaufmann brain age prediction algorithms to generate global and regional brain age estimates using T1 weighted magnetic resonance imaging (MRI) scans. We used linear mixed effects models to compare global and regional (FreeSurfer lobestrict output) BAG (i.e. predicted minus chronological age) between individuals with one of five primary substance use disorders as well as healthy controls. Alcohol use disorder (β = -5.49, t = -5.51, p < 0.001) was associated with higher global BAG, whereas amphetamine-type stimulant use disorder (β = 3.44, t = 2.42, p = 0.02) was associated with lower global BAG in the separate substance-specific models. People with alcohol use disorder appear to have a higher brain-age gap than people without alcohol use disorder, which is consistent with other evidence of the negative impact of alcohol on the brain.

Brain volumes and cortical thickness and associations with cognition in children born extremely preterm.

Children born extremely preterm (EPT) have altered brain volumes and cortical thickness and lower cognition than children born at term. Associations between these have remained largely unexplored, due to the lack of studies focusing on children born EPT. Children underwent brain magnetic resonance imaging (MRI) at term and/or 10 years and cognitive assessments at 12 years. The study comprised of 42 children born EPT and 29 term-born controls with cognitive data and MRI data at 10 years, 25 children born EPT had MRI data at term age and 20 had longitudinal MRI data. Cognition was positively associated with brain volumes at 10 years, but negatively associated with cortical thickness at 10 years. Most associations between term age brain volumes and cognitive outcomes were non-significant for children born EPT. Growth from term to 10 years in children born EPT was not associated with cognition. Insular volume was positively associated with cognition in children born EPT. Imaging assessments at 10 years had similar associations to cognition in children born EPT and term-born controls. Insular volume could be a biomarker for cognitive outcome. Associations between brain volumetric growth and cognition require further investigation. This study investigated brain volumes, volumetric growth, and cortical thickness in children born extremely preterm, who have rarely been studied exclusively, and compared the data with term-born controls. In both groups, brain volumes at 10 years were positively associated with cognitive outcome at 12 years, but cortical thickness at 10 years was negatively associated with cognitive outcome at 12 years. Volumetric growth from term age to 10 years was not associated with cognitive outcome in the subset of children born extremely preterm with longitudinal data. Insular volume may be a potential biomarker for cognitive outcome in children born extremely preterm.

Pregnancy history and estradiol influence spatial memory, hippocampal plasticity, and inflammation in middle-aged rats

Pregnancy and motherhood can have long-term effects on cognition and brain aging in both humans and rodents. Estrogens are related to cognitive function and neuroplasticity. Estrogens can improve cognition in postmenopausal women, but the evidence is mixed, partly due to differences in age of initiation, type of menopause, dose, formulation and route of administration. Additionally, past pregnancy influences brain aging and cognition as a younger age of first pregnancy in humans is associated with poorer aging outcomes. However, few animal studies have examined specific features of pregnancy history or the possible mechanisms underlying these changes. We examined whether maternal age at first pregnancy and estradiol differentially affected hippocampal neuroplasticity, inflammation, spatial reference cognition, and immediate early gene activation in response to spatial memory retrieval in middle-age. Thirteen-month-old rats (who were nulliparous (never mothered) or previously primiparous (had a litter) at three or seven months) received daily injections of estradiol (or vehicle) for sixteen days and were tested on the Morris Water Maze. An older age of first pregnancy was associated with impaired spatial memory but improved performance on reversal training, and increased number of new neurons in the ventral hippocampus. Estradiol decreased activation of new neurons in the dorsal hippocampus, regardless of parity history. Estradiol also decreased the production of anti-inflammatory cytokines based on age of first pregnancy. This work suggests that estradiol affects neuroplasticity and neuroinflammation in middle age, and that age of first pregnancy can have long lasting effects on hippocampus structure and function.

Amyloid-β Pathology Is the Common Nominator Proteinopathy of the Primate Brain Aging.

Senile plaques, mainly diffuse, and cerebral amyloid-β (Aβ) angiopathy are prevalent in the aging brain of non-human primates, from lemurs to non-human Hominidae. Aβ but not hyper-phosphorylated tau (HPtau) pathology is the common nominator proteinopathy of non-human primate brain aging. The abundance of Aβ in the aging primate brain is well tolerated, and the impact on cognitive functions is usually limited to particular tasks. In contrast, human brain aging is characterized by the early appearance of HPtau pathology, mainly forming neurofibrillary tangles, dystrophic neurites of neuritic plaques, and neuropil threads, preceding Aβ deposits by several decades and by its severity progressing from selected nuclei of the brain stem, entorhinal cortex, and hippocampus to the limbic system, neocortex, and other brain regions. Neurofibrillary tangles correlate with cognitive impairment and dementia in advanced cases. Aβ pathology is linked in humans to altered membrane protein and lipid composition, particularly involving lipid rafts. Although similar membrane alterations are unknown in non-human primates, membrane senescence is postulated to cause the activated β-amyloidogenic pathway, and Aβ pathology is the prevailing signature of non-human and human primate brain aging.

Delaying Brain Aging or Decreasing Tau Levels as Strategies to Prevent Alzheimer's Disease: In Memoriam of Mark A. Smith.

Aging is the main risk for neurodegenerative disorders like Alzheimer's disease. In this short review, I will comment on how delaying brain aging through the addition of Yamanaka Factors or small compounds that bind to the folate receptor alpha, which promote the expression of the Yamanaka Factors or by the decrease tau levels in brain cells from older subjects could serve as strategies to prevent Alzheimer's disease.

Characterization of Ptau181 Among a Diverse Community-Based Cohort: A HABS-HD Study.

Examination of Alzheimer's disease (AD) related biomarkers among diverse communities has remained limited. The aim of this study was to expand on prior work to provide a characterization of ptau181 among a diverse community sample. Consideration was taken regarding the impact of comorbidities on ptau181 levels including medical. 3,228 (n = 770 African American [AA], n = 1,231 Hispanic, and n = 1,227 non-Hispanic white [NHW]) Health and Aging Brain Study- Health Disparities (HABS-HD) participants were included in this study. ANCOVAs were conducted to examine differences in ptau181 levels across race and ethnic groups. Violin plots were also generated stratified by APOEɛ4 carrier status, Amyloid PET positivity status, medical comorbidity (hypertension, dyslipidemia, chronic kidney disease [CKD], and diabetes) and by cognitive diagnosis. Ptau181 levels were found to differ between Hispanics and NHW after covarying for age, sex, and APOEɛ4 status. Amyloid PET positivity was associated with higher ptau181 levels across all groups. APOEɛ4 positivity status was only significantly associated with ptau181 levels among AAs. Across all race and ethnic groups, those with a diagnosis of CKD had higher levels of ptau181. When stratified by cognitive diagnosis, cognitively unimpaired Hispanics had higher ptau181 if they also had a diagnosis of CKD or diabetes. p-values ≤0.01. Differences in ptau181 levels were shown in a diverse community sample. Medical comorbidities had a differing effect on ptau181 levels particularly among Hispanics even without cognitive impairment. Findings support the need for future work to consider comorbid conditions when examining the utility of ptau181.

White matter brain-age in diverse forms of epilepsy and interictal psychosis

Abnormal brain aging is suggested in epilepsy. Given the brain network dysfunction in epilepsy, the white matter tracts, which primarily interconnect brain regions, could be of special importance. We focused on white matter brain aging in diverse forms of epilepsy and comorbid psychosis. We obtained brain diffusion tensor imaging (DTI) data at 3 T-MRI in 257 patients with epilepsy and 429 healthy subjects. The tract-based fractional anisotropy values of the healthy subjects were used to build a brain-age prediction model, and we calculated the brain-predicted age difference (brain-PAD: predicted age—chronological age) of all subjects. As a result, almost all epilepsy categories showed significantly increased brain-PAD (p < 0.001), including temporal lobe epilepsy (TLE) with no MRI-lesion (+ 4.2 yr), TLE with hippocampal sclerosis (+ 9.1 yr), extratemporal focal epilepsy (+ 5.1 yr), epileptic encephalopathy or progressive myoclonus epilepsy (+ 18.4 yr), except for idiopathic generalized epilepsy (IGE). Patients with psychogenic non-epileptic seizures also presented increased brain-PAD. In TLE, interictal psychosis significantly raised brain-PAD by 8.7 years. In conclusion, we observed increased brain aging in most types of epilepsy, which was generally consistent with brain morphological aging results in previous studies. Psychosis may accelerate brain aging in TLE. These findings may suggest abnormal aging mechanisms in epilepsy and comorbid psychotic symptoms.

Obesity and brain volumes: mediation by cardiometabolic and inflammatory measures

BackgroundThis study aimed to investigate the relationship between overall obesity, central obesity and brain volumes, as well as to determine the extent to which cardiometabolic and inflammatory measures act as...