Polygenic risk discriminates Lewy body dementia from Alzheimer's disease.

Introduction: Lewy body dementia (LBD) shares genetic risk factors with Alzheimer's disease (AD), including apolipoprotein E (APOE), but is distinguishable at the genome-wide level. Polygenic risk scores (PRS) may therefore improve diagnostic classification.

Methods: We assessed diagnostic classification using AD-PRS excluding APOE (AD-PRS ), APOE risk score (APOE-RS), and plasma phosphorylated tau 181 (p-tau181), in 83 participants with LBD, 27 with positron emission tomography amyloid beta (Aβ)positive mild cognitive impairment or AD (MCI+/AD), and 57 controls.

Depressive Symptoms and Amyloid Pathology.

Importance: Depressive symptoms are associated with cognitive decline in older individuals. Uncertainty about underlying mechanisms hampers diagnostic and therapeutic efforts. This large-scale study aimed to elucidate the association between depressive symptoms and amyloid pathology.

PET Imaging of a Transgenic Tau Rat Model SHR24 with [F]AV1451.

Purpose: Positron Emission Tomography (PET) scans with radioligands targeting tau neurofibrillary tangles (NFT) have accelerated our understanding of the role of misfolded tau in neurodegeneration. While intended for human research, applying these radioligands to small animals establishes a vital translational link. Transgenic animal models of dementia, such as the tau rat SHR24, play a crucial role in enhancing our understanding of these disorders.

Connectional differences between humans and macaques in the MT+ complex.

MT+ is pivotal in the dorsal visual stream, encoding tool-use characteristics such as motion speed and direction. Despite its conservation between humans and monkeys, differences in MT+ spatial location and organization may lead to divergent, yet unexplored, connectivity patterns and functional characteristics. Using diffusion tensor imaging, we examined the structural connectivity of MT+ subregions in macaques and humans.

Longitudinal Assessment of Abnormal Cortical Folding in Fetuses and Neonates With Isolated Non-Severe Ventriculomegaly.

Purpose: The impact of ventriculomegaly (VM) on cortical development and brain functionality has been extensively explored in existing literature. VM has been associated with higher risks of attention-deficit and hyperactivity disorders, as well as cognitive, language, and behavior deficits. Some studies have also shown a relationship between VM and cortical overgrowth, along with reduced cortical folding, both in fetuses and neonates.

Long-chain omega-3 polyunsaturated fatty acids are associated with brain connectivity and mood in young adults with subthreshold depression: A preliminary study.

Background: The long-chain omega-3 polyunsaturated fatty acids (PUFAs) docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) have beneficial effects in depression, and these effects may be mediated via changes in functional brain connectivity. However, little is known about these effects in those with subthreshold depression.

Methods: 15 Participants aged 18-29 years with Patient Health Questionnaire-8 (PHQ-8) scores ≥ 4 and Generalised Anxiety Disorder Assessment-7 (GAD-7) scores ≥ 5, underwent resting-state functional magnetic resonance imaging.

Temporal Lobe Epilepsy Perturbs the Brain-Wide Excitation-Inhibition Balance: Associations with Microcircuit Organization, Clinical Parameters, and Cognitive Dysfunction.

Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with ample research focusing on elucidating its cellular manifestations. However, few studies investigate E/I imbalance at the macroscale, whole-brain level, and its microcircuit-level mechanisms and clinical significance remain incompletely understood. Here, the Hurst exponent, an index of the E/I ratio, is computed from resting-state fMRI time series, and microcircuit parameters are simulated using biophysical models.

Robust and interpretable AI-guided marker for early dementia prediction in real-world clinical settings.

Background: Predicting dementia early has major implications for clinical management and patient outcomes. Yet, we still lack sensitive tools for stratifying patients early, resulting in patients being undiagnosed or wrongly diagnosed. Despite rapid expansion in machine learning models for dementia prediction, limited model interpretability and generalizability impede translation to the clinic.

Disentangling the effect of sex from brain size on brain organization and cognitive functioning.

Neuroanatomical sex differences estimated in neuroimaging studies are confounded by total intracranial volume (TIV) as a major biological factor. Employing a matching approach widely used for causal modeling, we disentangled the effect of TIV from sex to study sex-differentiated brain aging trajectories, their relation to functional networks and cytoarchitectonic classes, brain allometry, and cognition. Using data from the UK Biobank, we created subsamples that removed, maintained, or exaggerated the TIV differences in the original sample.

The brain selectively allocates energy to functional brain networks under cognitive control.

Network energy has been conceptualized based on structural balance theory in the physics of complex networks. We utilized this framework to assess the energy of functional brain networks under cognitive control and to understand how energy is allocated across canonical functional networks during various cognitive control tasks. We extracted network energy from functional connectivity patterns of subjects who underwent fMRI scans during cognitive tasks involving working memory, inhibitory control, and cognitive flexibility, in addition to task-free scans.

Associations between genetic variations in oxytocin pathway genes and hippocampal volume: Insights from the UK Biobank.

The role of oxytocin-related genes in social-cognitive function has been previously established, but structural brain mechanisms underlying this link remain poorly understood. Utilizing a substantial dataset from the UK Biobank (N ≈ 30,000), this research determined associations between variations in ten single nucleotide polymorphisms (SNPs) within three oxytocin pathway genes (i.e.

Comparison of different group-level templates in gradient-based multimodal connectivity analysis.

The study of large-scale brain connectivity is increasingly adopting unsupervised approaches that derive low-dimensional spatial representations from high-dimensional connectomes, referred to as gradient analysis. When translating this approach to study interindividual variations in connectivity, one technical issue pertains to the selection of an appropriate group-level template to which individual gradients are aligned. Here, we compared different group-level template construction strategies using functional and structural connectome data from neurotypical controls and individuals with autism spectrum disorder (ASD) to identify between-group differences.

Multi-Night Electroencephalography Reveals Positive Association Between Sleep Efficiency and Hippocampal Subfield and Entorhinal Cortex Volumes in Healthy Aging.

Age-related atrophy of the human hippocampus and the enthorinal cortex starts accelerating at around age 60. Due to the contributions of these regions to many cognitive functions seamlessly used in everyday life, this can heavily impact the lives of elderly people. The hippocampus is not a unitary structure, and mechanisms of its age-related decline appear to differentially affect its subfields.

Predicting recovery in patients with mild traumatic brain injury and a normal CT using serum biomarkers and diffusion tensor imaging (CENTER-TBI): an observational cohort study.

Background: Even patients with normal computed tomography (CT) head imaging may experience persistent symptoms for months to years after mild traumatic brain injury (mTBI). There is currently no good way to predict recovery and triage patients who may benefit from early follow-up and targeted intervention. We aimed to assess if existing prognostic models can be improved by serum biomarkers or diffusion tensor imaging metrics (DTI) from MRI, and if serum biomarkers can identify patients for DTI.

Association between phenotypic age and mortality risk in individuals with obesity: a retrospective cohort study.

Objective: This study investigates the association between phenotypic age acceleration (PAA) and all-cause and cause-specific mortality in obese individuals.

Methods: Data were drawn from the National Health and Nutrition Examination Survey (NHANES) between 1999 and 2018, including 9,925 obese adults (BMI ≥ 30 kg/m). PAA, defined as phenotypic age exceeding chronological age, was assessed using clinical biomarkers.

Comparison of Plasma p-tau217 and [F]FDG-PET for Identifying Alzheimer Disease in People With Early-Onset or Atypical Dementia.

Background And Objectives: To compare the diagnostic performance of an immunoassay for plasma concentrations of phosphorylated tau (p-tau) 217 with visual assessments of fluorine-18 fluorodeoxyglucose [F]FDG-PET in individuals who meet appropriate use criteria for Alzheimer dementia (AD) biomarker assessments.

Methods: We performed a retrospective analysis of individuals with early-onset (age <65 years at onset) and/or atypical dementia (features other than memory at onset), who were evaluated at a tertiary care memory clinic. All participants underwent measurements of CSF biomarkers (Aβ42, p-tau181, and total tau levels), as well as [F]FDG-PET scans, amyloid-PET scans, and plasma p-tau217 quantifications.

Biological brain age and resilience in cognitively unimpaired 70-year-old individuals.

Introduction: This study investigated the associations of brain age gap (BAG)-a biological marker of brain resilience-with life exposures, neuroimaging measures, biological processes, and cognitive function.

Methods: We derived BAG by subtracting predicted brain age from chronological age in 739 septuagenarians without dementia or neurological disorders. Robust linear regression models assessed BAG associations with life exposures, plasma inflammatory and metabolic biomarkers, magnetic resonance imaging, and cerebrospinal fluid biomarkers of neurodegeneration and vascular brain injury, and cognitive performance.

A Machine Learning Model to Harmonize Volumetric Brain MRI Data for Quantitative Neuroradiologic Assessment of Alzheimer Disease.

Purpose To extend a previously developed machine learning algorithm for harmonizing brain volumetric data of individuals undergoing neuroradiologic assessment of Alzheimer disease not encountered during model training. Materials and Methods Neuroharmony is a recently developed method that uses image quality metrics as predictors to remove scanner-related effects in brain-volumetric data using random forest regression. To account for the interactions between Alzheimer disease pathology and image quality metrics during harmonization, the authors developed a multiclass extension of Neuroharmony for individuals with and without cognitive impairment.

Extra-axial inflammatory signal and its relationship to peripheral and central immunity in depression.

Although both central and peripheral inflammation have been observed consistently in depression, the relationship between the two remains obscure. Extra-axial immune cells may play a role in mediating the connection between central and peripheral immunity. This study investigates the potential roles of calvarial bone marrow and parameningeal spaces in mediating interactions between central and peripheral immunity in depression.

High throughput in-line content uniformity measurement of tablets based on real-time UV imaging.

This paper presents a precursor of a novel, high-throughput, in-line system, which utilizes ultraviolet (UV) imaging in order to predict the active pharmaceutical ingredient (API) content of tablets in real-time, non-destructive manner. Pimobendan, cardiovascular drug used in veterinary medicine was chosen as a fluorescent model API. Two experiments were carried out using different measurement setups, where the tablets were moving at different speeds.

Impact of a national dementia research consortium: The Canadian Consortium on Neurodegeneration in Aging (CCNA).

The Canadian Consortium on Neurodegeneration in Aging (CCNA) was created by the Canadian federal government through its health research funding agency, the Canadian Institutes for Health Research (CIHR), in 2014, as a response to the G7 initiative to fight dementia. Two five-year funding cycles (2014-2019; 2019-2024) have occurred following peer review, and a third cycle (Phase 3) has just begun. A unique construct was mandated, consisting of 20 national teams in Phase I and 19 teams in Phase II (with research topics spanning from basic to clinical science to health resource systems) along with cross-cutting programs to support them.

Multimodal neural correlates of childhood psychopathology.

Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology () factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures.

Detecting and Tracking β-Amyloid Oligomeric Forms and Dynamics In Vitro by a High-Sensitivity Fluorescent-Based Assay.

Aggregation of β-amyloid protein is a hallmark pathology of the neurodegenerative disorder Alzheimer's disease and proceeds from monomers to insoluble misfolded fibril forms via soluble and highly toxic oligomeric intermediates. Given the dual feature of being the most toxic form of the Aβ aggregate proteome and an early marker of pathogenesis, there is a need for sensitive methods that can be used to detect Aβ oligomers and investigate the dynamics of aggregation. Herein, we describe a method based on the application of an oligomer-sensitive fluorescent chemical probe pTP-TFE combined with the use of a QIAD (Quantitative determination of Interference with Aβ Aggregate Size Distribution) assay to correctly identify Aβ oligomers in high sensitivity.