Ageing and brain white matter structure in 3,513 UK Biobank participants

Heterogeneity of mature oligodendrocytes in the central nervous system

Mature oligodendrocytes form myelin sheaths that are crucial for the insulation of axons and efficient signal transmission in the central nervous system. Recent evidence has challenged the classical view of the functionally static mature oligodendrocyte and revealed a gamut of dynamic functions such as the ability to modulate neuronal circuitry and provide metabolic support to axons. Despite the recognition of potential heterogeneity in mature oligodendrocyte function, a comprehensive summary of mature oligodendrocyte diversity is lacking. We delve into early 20 th -century studies by Robertson and Río-Hortega that laid the foundation for the modern identification of regional and morphological heterogeneity in mature oligodendrocytes. Indeed, recent morphologic and functional studies call into question the long-assumed homogeneity of mature oligodendrocyte function through the identification of distinct subtypes with varying myelination preferences. Furthermore, modern molecular investigations, employing techniques such as single cell/nucleus RNA sequencing, consistently unveil at least six mature oligodendrocyte subpopulations in the human central nervous system that are highly transcriptomically diverse and vary with central nervous system region. Age and disease related mature oligodendrocyte variation denotes the impact of pathological conditions such as multiple sclerosis, Alzheimer's disease, and psychiatric disorders. Nevertheless, caution is warranted when subclassifying mature oligodendrocytes because of the simplification needed to make conclusions about cell identity from temporally confined investigations. Future studies leveraging advanced techniques like spatial transcriptomics and single-cell proteomics promise a more nuanced understanding of mature oligodendrocyte heterogeneity. Such research avenues that precisely evaluate mature oligodendrocyte heterogeneity with care to understand the mitigating influence of species, sex, central nervous system region, age, and disease, hold promise for the development of therapeutic interventions targeting varied central nervous system pathology.

Multimodal brain age prediction using machine learning: combining structural MRI and 5-HT2AR PET-derived features

To better assess the pathology of neurodegenerative disorders and the efficacy of neuroprotective interventions, it is necessary to develop biomarkers that can accurately capture age-related biological changes in the human brain. Brain serotonin 2A receptors (5-HT2AR) show a particularly profound age-related decline and are also reduced in neurodegenerative disorders, such as Alzheimer's disease. This study investigates whether the decline in 5-HT2AR binding, measured in vivo using positron emission tomography (PET), can be used as a biomarker for brain aging. Specifically, we aim to (1) predict brain age using 5-HT2AR binding outcomes, (2) compare 5-HT2AR-based predictions of brain age to predictions based on gray matter (GM) volume, as determined with structural magnetic resonance imaging (MRI), and (3) investigate whether combining 5-HT2AR and GM volume data improves prediction. We used PET and MR images from 209 healthy individuals aged between 18 and 85 years (mean = 38, std = 18) and estimated 5-HT2AR binding and GM volume for 14 cortical and subcortical regions. Different machine learning algorithms were applied to predict chronological age based on 5-HT2AR binding, GM volume, and the combined measures. The mean absolute error (MAE) and a cross-validation approach were used for evaluation and model comparison. We find that both the cerebral 5-HT2AR binding (mean MAE = 6.63 years, std = 0.74 years) and GM volume (mean MAE = 6.95 years, std = 0.83 years) predict chronological age accurately. Combining the two measures improves the prediction further (mean MAE = 5.54 years, std = 0.68). In conclusion, 5-HT2AR binding measured using PET might be useful for improving the quantification of a biomarker for brain aging.

Additive effects of mild head trauma, blast exposure, and aging within white matter tracts: A novel Diffusion Tensor Imaging analysis approach

Existing diffusion tensor imaging (DTI) studies of neurological injury following high-level blast exposure (hlBE) in military personnel have produced widely variable results. This is potentially due to prior studies often not considering the quantity and/or recency of hlBE, as well as co-morbidity with non-blast head trauma (nbHT). Herein, we compare commonly used DTI metrics: fractional anisotropy and mean, axial, and radial diffusivity, in Veterans with and without history of hlBE and/or nbHT. We use both the traditional method of dividing participants into 2 equally weighted groups and an alternative method wherein each participant is weighted by quantity and recency of hlBE and/or nbHT. While no differences were detected using the traditional method, the alternative method revealed diffuse and extensive changes in all DTI metrics. These effects were quantified within 43 anatomically defined white matter tracts, which identified the forceps minor, middle corpus callosum, acoustic and optic radiations, fornix, uncinate, inferior fronto-occipital and inferior longitudinal fasciculi, and cingulum, as the pathways most affected by hlBE and nbHT. Moreover, additive effects of aging were present in many of the same tracts suggesting that these neuroanatomical effects may compound with age.

Trem2-deficiency aggravates and accelerates age-related myelin degeneration

Aging is the greatest known risk factor for most neurodegenerative diseases. Myelin degeneration is an early pathological indicator of these diseases and a normal part of aging; albeit, to a lesser extent. Despite this, little is known about the contribution of age-related myelin degeneration on neurodegenerative disease. Microglia participate in modulating white matter events from demyelination to remyelination, including regulation of (de)myelination by the microglial innate immune receptor triggering receptor expressed on myeloid cells 2 (TREM2). Here, we demonstrate Trem2-deficiency aggravates and accelerates age-related myelin degeneration in the striatum. We show TREM2 is necessary for remyelination by recruiting reparative glia and mediating signaling that promotes OPC differentiation/maturation. In response to demyelination, TREM2 is required for phagocytosis of large volumes of myelin debris. In addition to lysosomal regulation, we show TREM2 can modify the ER stress response, even prior to overt myelin debris, that prevents lipid accumulation and microglial dysfunction. These data support a role for Trem2-dependent interactions in age-related myelin degeneration and suggest a basis for how early dysfunctional microglia could contribute to disease pathology through insufficent repair, defective phagocytosis, and the ER stress response.

Functional correlation tensors in brain white matter and the effects of normal aging

Resting state correlations between blood oxygenation level dependent (BOLD) MRI signals from voxels in white matter (WM) are demonstrably anisotropic, so that functional correlation tensors (FCT) may be used to quantify the underlying microstructure of BOLD effects in WM tracts. However, the overall spatial distribution of FCTs and their metrics in specific populations has not yet been established, and the factors that affect their precise arrangements remain unclear. Changes in WM occur with normal aging, and these may be expected to affect FCTs. We hypothesized that FCTs exhibit a characteristic spatial pattern and may show systematic changes with aging or other factors. Here we report our analyses of the FCT characteristics of fMRI images of a large cohort of 461 cognitively normal subjects (190 females, 271 males) sourced from the Open Access Series of Imaging Studies (OASIS), with age distributions of 42 y/o - 95 y/o. Group averages and statistics of FCT indices, including axial functional correlations, radial functional correlations, mean functional correlations and fractional anisotropy, were quantified in WM bundles defined by the JHU ICBM-DTI-81 WM atlas. In addition, their variations with normal aging were examined. The results revealed a dimorphic distribution of changes in FCT metrics with age, with decreases of the functional correlations in some regions and increases in others. Supplementary analysis revealed that females exhibited significant age effects on a greater number of WM areas, but the interaction between age and sex was not significant. The findings demonstrate the reproducibility of the spatial distribution of FCT metrics and reveal subtle regional changes with age.

Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review

Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.

Sex-related variability of white matter tracts in the whole HCP cohort

Behavioral differences between men and women have been studied extensively, as have differences in brain anatomy. However, most studies have focused on differences in gray matter, while white matter has been much less studied. We conducted a comprehensive study of 77 deep white matter tracts to analyze their volumetric and microstructural variability between men and women in the full Human Connectome Project (HCP) cohort of 1065 healthy individuals aged 22-35 years. We found a significant difference in total brain volume between men and women (+ 12.6% in men), consistent with the literature. 16 tracts showed significant volumetric differences between men and women, one of which stood out due to a larger effect size: the corpus callosum genu, which was larger in women (+ 7.3% in women, p = 5.76 × 10-19). In addition, we found several differences in microstructural parameters between men and women, both using standard Diffusion Tensor Imaging (DTI) parameters and more complex microstructural parameters from the Neurite Orientation Dispersion and Density Imaging (NODDI) model, with the tracts showing the greatest differences belonging to motor (cortico-spinal tracts, cortico-cerebellar tracts) or limbic (cingulum, fornix, thalamo-temporal radiations) systems. These microstructural differences may be related to known behavioral differences between the sexes in timed motor performance, aggressiveness/impulsivity, and social cognition.

Patterns of cerebral damage in multiple sclerosis and aquaporin-4 antibody-positive neuromyelitis optica spectrum disorders-major differences revealed by non-conventional imaging

Multiple sclerosis and aquaporin-4 antibody neuromyelitis optica spectrum disorders are distinct autoimmune CNS disorders with overlapping clinical features but differing pathology. Multiple sclerosis is primarily a demyelinating disease with the presence of widespread axonal damage, while neuromyelitis optica spectrum disorders is characterized by astrocyte injury with secondary demyelination. Diagnosis is typically based on lesion characteristics observed on standard MRI imaging and antibody testing but can be challenging in patients with in-between clinical presentations. Non-conventional MRI techniques can provide valuable diagnostic information by measuring disease processes at the microstructural level. We used non-conventional MRI to measure markers of axonal loss in specific white matter tracts in multiple sclerosis and neuromyelitis optica spectrum disorders, depending on their relationship with focal lesions. Patients with relapsing-remitting multiple sclerosis (n = 20), aquaporin-4 antibody-associated neuromyelitis optica spectrum disorders (n = 20) and healthy controls (n = 20) underwent a 3T brain MRI, including T1-, T2- and diffusion-weighted sequences, quantitative susceptibility mapping and phase-sensitive inversion recovery sequence. Tractometry was used to differentiate tract fibres traversing through white matter lesions from those that did not. Neurite density index was assessed using neurite orientation dispersion and density imaging model. Cortical damage was evaluated using T1 relaxation rates. Cortical lesions and paramagnetic rim lesions were identified using phase-sensitive inversion recovery and quantitative susceptibility mapping. In tracts traversing lesions, only one out of 50 tracts showed a decreased neurite density index in multiple sclerosis compared with neuromyelitis optica spectrum disorders. Among 50 tracts not traversing lesions, six showed reduced neurite density in multiple sclerosis (including three in the cerebellum and brainstem) compared to neuromyelitis optica spectrum disorders. In multiple sclerosis, reduced neurite density was found in the majority of fibres traversing (40/50) and not traversing (37/50) white matter lesions when compared to healthy controls. A negative correlation between neurite density in lesion-free fibres and cortical lesions, but not paramagnetic rim lesions, was observed in multiple sclerosis (39/50 tracts). In neuromyelitis optica spectrum disorders compared to healthy controls, decreased neurite density was observed in a subset of fibres traversing white matter lesions, but not in lesion-free fibres. In conclusion, we identified significant differences between multiple sclerosis and neuromyelitis optica spectrum disorders corresponding to their distinct pathologies. Specifically, in multiple sclerosis, neurite density reduction was widespread across fibres, regardless of their relationship to white matter lesions, while in neuromyelitis optica spectrum disorders, this reduction was limited to fibres passing through white matter lesions. Further studies are needed to evaluate the discriminatory potential of neurite density measures in white matter tracts for differentiating multiple sclerosis from neuromyelitis optica spectrum disorders.

Testing retrogenesis and physiological explanations for tract-wise white matter aging: links to developmental order, fibre calibre, and vascularization

To understand the consistently observed spatial distribution of white-matter (WM) aging, developmentally driven theories termed "retrogenesis" have gained traction, positing that the order of WM tract development predicts the order of declines. Regions that develop first are expected to deteriorate the last, i.e. "last-in-first-out". Alternatively, regions which develop most rapidly may also decline most rapidly in aging, or "gains-predict-loss". The validity of such theories remains uncertain, in part due to lack of clarity on the definition of developmental order. Importantly, our recent findings suggest that WM aging is also associated with physiological parameters such as perfusion, which may be linked to fibre metabolic need, which in turn varies with fibre size. Here we address the extent to which the degree of WM aging is determined by development trajectory (i.e. retrogenesis) and/or by physiological state. We obtained microstructural and perfusion measures using data from the Human Connectome Project in Aging (HCP-A), complemented by a meta-analysis involving maps of fibre calibre and macrovascular volume. Our results suggest that (1) while tracts that appear last or finish myelinating first in development display the slowest aging, the pattern of aging is not fully explained by retrogenesis; in fact, time courses of tract emergence and myelination give rise to opposite associations with WM decline; (2) tracts that appear earlier also have higher mean axon calibre and are also associated with lower degrees of WM microstructural aging; (3) such tracts also tend to exhibit relatively sustained CBF with a higher rate of lengthening of the arterial transit times (ATT), suggestive of collateral blood supply. These findings were also sex dependent in a tract-specific manner. Future work will investigate whether these are ultimately influenced by each tract's metabolic demand and the role of macrovascular collateral flow.

What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review

ABSTRACT

Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.

Brain aging patterns in a large and diverse cohort of 49,482 individuals

Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.

Discovering the effective connectome of the brain with dynamic Bayesian DAG learning

Understanding the complex mechanisms of the brain can be unraveled by extracting the Dynamic Effective Connectome (DEC). Recently, score-based Directed Acyclic Graph (DAG) discovery methods have shown significant improvements in extracting the causal structure and inferring effective connectivity. However, learning DEC through these methods still faces two main challenges: one with the fundamental impotence of high-dimensional dynamic DAG discovery methods and the other with the low quality of fMRI data. In this paper, we introduce Bayesian Dynamic DAG learning with M-matrices Acyclicity characterization (BDyMA) method to address the challenges in discovering DEC. The presented dynamic DAG enables us to discover direct feedback loop edges as well. Leveraging an unconstrained framework in the BDyMA method leads to more accurate results in detecting high-dimensional networks, achieving sparser outcomes, making it particularly suitable for extracting DEC. Additionally, the score function of the BDyMA method allows the incorporation of prior knowledge into the process of dynamic causal discovery which further enhances the accuracy of results. Comprehensive simulations on synthetic data and experiments on Human Connectome Project (HCP) data demonstrate that our method can handle both of the two main challenges, yielding more accurate and reliable DEC compared to state-of-the-art and traditional methods. Additionally, we investigate the trustworthiness of DTI data as prior knowledge for DEC discovery and show the improvements in DEC discovery when the DTI data is incorporated into the process.

Microstructural brain assessment in late-life depression and apathy using diffusion MRI multi-compartments models and tractometry

Late-life depression (LLD) is both common and disabling and doubles the risk of dementia onset. Apathy might constitute an additional risk of cognitive decline but clear understanding of its pathophysiology is lacking. While white matter (WM) alterations have been assessed using diffusion tensor imaging (DTI), this model cannot accurately represent WM microstructure. We hypothesized that a more complex multi-compartment model would provide new biomarkers of LLD and apathy. Fifty-six individuals (LLD n = 35, 26 females, 75.2 ± 6.4 years, apathy evaluation scale scores (41.8 ± 8.7) and Healthy controls, n = 21, 16 females, 74.7 ± 5.2 years) were included. In this article, a tract-based approach was conducted to investigate novel diffusion model biomarkers of LLD and apathy by interpolating microstructural metrics directly along the fiber bundle. We performed multivariate statistical analysis, combined with principal component analysis for dimensional data reduction. We then tested the utility of our framework by demonstrating classically reported from the literature modifications in LDD while reporting new results of biological-basis of apathy in LLD. Finally, we aimed to investigate the relationship between apathy and microstructure in different fiber bundles. Our study suggests that new fiber bundles, such as the striato-premotor tracts, may be involved in LLD and apathy, which bring new light of apathy mechanisms in major depression. We also identified statistical changes in diffusion MRI metrics in 5 different tracts, previously reported in major cognitive disorders dementia, suggesting that these alterations among these tracts are both involved in motivation and cognition and might explain how apathy is a prodromal phase of degenerative disorders.

Associations of long-term exposure to low-level PM2.5 and brain disorders in 260,922 middle-aged and older adults

Long-term exposure to high-level ambient PM2.5 was associated with increased risks of brain disorders, while the associations remain uncertain when the exposure is lower than current air quality standards in numerous countries. This study aimed to assess the effects of PM2.5 exposure on the brain system in the population with annual mean concentrations ≤15 μg/m3. We analyzed data from 260,922 participants without preexisting brain diseases at baseline in the UK Biobank. The geographical distribution of PM2.5 in 2010 was estimated by a land use regression model and linked with individual residential address. We investigated associations of ambient PM2.5 with incident neurological (dementia, Parkinson's diseases [PD], epilepsy, and migraine) and psychiatric (major depressive disorder [MDD] and anxiety disorder) diseases through Cox proportional hazard models. We further estimated the links with brain imaging phenotypes by neuroimaging analysis. Results showed that in the population with PM2.5 concentrations ≤15 μg/m3, each interquartile range (IQR, 1.28 μg/m3) increment in PM2.5 was related to incidence risks of dementia, epilepsy, migraine, MDD, and anxiety disorder with hazard ratios of 1.08 (95% confidence interval [CI]: 1.03, 1.13), 1.12 (1.05, 1.20), 1.07 (1.00, 1.13), 1.06 (1.03, 1.09), and 1.05 (1.02, 1.08), respectively. We did not observe a significant association with PD. The association with dementia was stronger among the population with poor cardiovascular health (measured by Life's Essential 8) than the counterpart (P for interaction = 0.037). Likewise, per IQR increase was associated with specific brain imaging phenotypes, including volumes of total brain (β = -0.036; 95% CI: -0.050, -0.022), white matter (-0.030; -0.046, -0.014), grey matter (-0.030; -0.042, -0.017), respectively. The findings suggest long-term exposure to ambient PM2.5 at low-level still has an adverse impact on the neuro-psychiatric systems. The brain-relevant epidemiological assessment suggests that each country should update the standard for ambient PM2.5 following the World Health Organization Air Quality Guidelines 2021.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics

The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Association of past and current sleep duration with structural brain differences: A large population-based study from the UK Biobank

OBJECTIVE

This study aimed to examine the association between past/current sleep duration and macro-/micro-structural brain outcomes and explore whether hypertension or social activity plays a role in such association.

METHODS

Within the UK Biobank, 40 436 dementia-free participants (age 40-70 years) underwent a baseline assessment followed by a brain magnetic resonance imaging (MRI) scan 9 years later. Past (baseline) and current (MRI scans) sleep duration (hours/day) were recorded and classified as short (≤5), intermediate (6-8), and long (≥9). Brain structural volumes and diffusion markers were assessed by MRI scans.

RESULTS

Compared with past intermediate sleep, past short sleep was related to smaller cortex volumes (standardized β [95 % CI]: -0.04 [-0.07, -0.02]) and lower regional fractional anisotropy (FA) (-0.08 [-0.13, -0.03]), while past long sleep was related to smaller regional subcortical volumes (standardized β: -0.04 to -0.07 for thalamus, accumbens, and hippocampus). Compared to current intermediate sleep, current short sleep was associated with smaller cortex volumes (-0.03 [-0.05, -0.01]), greater white matter hyperintensities (WMH) volumes (0.04 [0.01, 0.08]), and lower regional FA (-0.07 [-0.11, -0.02]). However, current long sleep was related to smaller total brain (-0.03 [-0.05, -0.02]), grey matter (-0.05 [-0.07, -0.03]), cortex (-0.05 [-0.07, -0.03]), regional subcortical volumes [standardized β: -0.05 to -0.09 for putamen, thalamus, hippocampus, and accumbens]), greater WMH volumes (0.06 [0.03, 0.09]), as well as lower regional FA (-0.05 [-0.09, -0.02]). The association between current long sleep duration and poor brain health was stronger among people with hypertension or low frequency of social activity (all Pinteraction <0.05).

CONCLUSIONS

Both past and current short/long sleep are associated with smaller brain volume and poorer white matter health in the brain, especially in individuals with hypertension and low frequency of social activity. Our findings highlight the need to maintain 6-8 h' sleep duration for healthy brain aging.

Neurocognitive and neurobehavioral mechanisms of change following psychological treatment for alcohol use disorder

BACKGROUND

Although modestly effective treatments exist for alcohol use disorder (AUD), many individuals return to heavy drinking after treatment, suggesting the need for better understanding of factors that contribute to maintaining abstinence or drinking reductions. Whereas past studies identified what treatments work for AUD, recent studies focus more on why particular treatments work, and the mechanisms by which treatment leads to change. This focus on mechanisms of behavior change (MOBC) may inform the process by which treatment leads to better outcomes, and also may lead to new treatments or modifications of existing treatments that target empirically supported mechanisms known to lead to change. There is a paucity of studies examining MOBC from a neurocognitive perspective.

METHOD

To address this gap in knowledge, the study described here is examining emotional reactivity, alcohol cue reactivity, and cognitive control as potential MOBC at three levels of analysis - self-report, behavior, and neural.

RESULTS

One hundred ten treatment-seeking individuals with an AUD are being randomized to receive 8 sessions of either Cognitive Behavioral Treatment (CBT) or Mindfulness Based Treatment (MBT) after up to 4 sessions of a platform treatment focused on enhancing motivation to change. To establish the temporal relationship between changes in drinking and changes in MOBC, patients are assessed at baseline, during and immediately after treatment, and 9- and 15-months post-baseline. Relationships between changes in drinking and changes in the proposed MOBC will be examined using advanced mixed modeling techniques.

CONCLUSIONS

Results should advance AUD treatment by targeting treatments to neurocognitive MOBC.

Superagers Resist Typical Age-Related White Matter Structural Changes

Superagers are elderly individuals with the memory ability of people 30 years younger and provide evidence that age-related cognitive decline is not inevitable. In a sample of 64 superagers (mean age, 81.9; 59% women) and 55 typical older adults (mean age, 82.4; 64% women) from the Vallecas Project, we studied, cross-sectionally and longitudinally over 5 years with yearly follow-ups, the global cerebral white matter status as well as region-specific white matter microstructure assessment derived from diffusivity measures. Superagers and typical older adults showed no difference in global white matter health (total white matter volume, Fazekas score, and lesions volume) cross-sectionally or longitudinally. However, analyses of diffusion parameters revealed the better white matter microstructure in superagers than in typical older adults. Cross-sectional differences showed higher fractional anisotropy (FA) in superagers mostly in frontal fibers and lower mean diffusivity (MD) in most white matter tracts, expressed as an anteroposterior gradient with greater group differences in anterior tracts. FA decrease over time is slower in superagers than in typical older adults in all white matter tracts assessed, which is mirrored by MD increases over time being slower in superagers than in typical older adults in all white matter tracts except for the corticospinal tract, the uncinate fasciculus, and the forceps minor. The better preservation of white matter microstructure in superagers relative to typical older adults supports resistance to age-related brain structural changes as a mechanism underpinning the remarkable memory capacity of superagers, while their regional aging pattern is in line with the last-in-first-out hypothesis.

Heterogeneity of morphometric similarity networks in health and schizophrenia

Introduction

Morphometric similarity is a recently developed neuroimaging phenotype of inter-regional connectivity by quantifying the similarity of a region to other regions based on multiple MRI parameters. Altered average morphometric similarity has been reported in psychotic disorders at the group level, with considerable heterogeneity across individuals. We used normative modeling to address cross-sectional and longitudinal inter-individual heterogeneity of morphometric similarity in health and schizophrenia.

Methods

Morphometric similarity for 62 cortical regions was obtained from baseline and follow-up T1-weighted scans of healthy individuals and patients with chronic schizophrenia. Cortical regions were classified into seven predefined brain functional networks. Using Bayesian Linear Regression and taking into account age, sex, image quality and scanner, we trained and validated normative models in healthy controls from eleven datasets (n = 4310). Individual deviations from the norm (z-scores) in morphometric similarity were computed for each participant for each network and region at both timepoints. A z-score ≧ than 1.96 was considered supra-normal and a z-score ≦ -1.96 infra-normal. As a longitudinal metric, we calculated the change over time of the total number of infra- or supra-normal regions per participant.

Results

At baseline, patients with schizophrenia had decreased morphometric similarity of the default mode network and increased morphometric similarity of the somatomotor network when compared with healthy controls. The percentage of patients with infra- or supra-normal values for any region at baseline and follow-up was low (<6%) and did not differ from healthy controls. Mean intra-group changes over time in the total number of infra- or supra-normal regions were small in schizophrenia and healthy control groups (<1) and there were no significant between-group differences.

Conclusions

In a case-control setting, a decrease of morphometric similarity within the default mode network may be a robust finding implicated in schizophrenia. However, normative modeling suggests that significant reductions and changes over time of regional morphometric similarity are evident only in a minority of patients.

White Matter Tract Integrity Is Reduced in Depression and in Individuals With Genetic Liability to Depression

BACKGROUND

While major depression has been linked to changes in white matter architecture, it remains unclear whether risk factors for depression are directly associated with these alterations. We reexamined white matter fiber tracts in individuals with depressive symptoms and investigated the connection between genetic and environmental risk for depression and structural changes in the brain.

METHODS

We included 19,183 participants from the UK Biobank imaging cohort, with depression status and adverse life experience based on questionnaire data and genetic liability for depression quantified by polygenic scores. The integrity of 27 white matter tracts was assessed using mean fractional anisotropy derived from diffusion magnetic resonance imaging.

RESULTS

White matter integrity was reduced, particularly in thalamic and intracortical fiber tracts, in individuals with depressive symptoms, independent of current symptom status. In a group of healthy individuals without depression, increasing genetic risk and increasing environmental risk were associated with reduced integrity in relevant fiber tracts, particularly in thalamic radiations. This association was stronger than expected based on statistical dependencies between samples, as confirmed by subsequent in silico simulations and permutation tests.

CONCLUSIONS

White matter alterations in thalamic and association tracts are associated with depressive symptoms and genetic risk for depression in unaffected individuals, suggesting an intermediate phenotype at the brain level.

Sex, racial, and APOE-ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease

INTRODUCTION

The effects of sex, race, and Apolipoprotein E (APOE) - Alzheimer's disease (AD) risk factors - on white matter integrity are not well characterized.

METHODS

Diffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 ± 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex, race, and APOE-ε4 carrier status.

RESULTS

Sex differences in FAFWcorr in association and projection tracts, racial differences in FAFWcorr in projection tracts, and APOE-ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced.

DISCUSSION

There are prominent differences in white matter microstructure by sex, race, and APOE-ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted.

Multi-organ imaging-derived polygenic indexes for brain and body health

The UK Biobank (UKB) imaging project is a crucial resource for biomedical research, but is limited to 100,000 participants due to cost and accessibility barriers. Here we used genetic data to predict heritable imaging-derived phenotypes (IDPs) for a larger cohort. We developed and evaluated 4,375 IDP genetic scores (IGS) derived from UKB brain and body images. When applied to UKB participants who were not imaged, IGS revealed links to numerous phenotypes and stratified participants at increased risk for both brain and somatic diseases. For example, IGS identified individuals at higher risk for Alzheimer's disease and multiple sclerosis, offering additional insights beyond traditional polygenic risk scores of these diseases. When applied to independent external cohorts, IGS also stratified those at high disease risk in the All of Us Research Program and the Alzheimer's Disease Neuroimaging Initiative study. Our results demonstrate that, while the UKB imaging cohort is largely healthy and may not be the most enriched for disease risk management, it holds immense potential for stratifying the risk of various brain and body diseases in broader external genetic cohorts.

Probing Evidence of Cerebral White Matter Microstructural Disruptions in Ischemic Heart Disease Before and Following Cardiac Rehabilitation: A Diffusion Tensor MR Imaging Study

BACKGROUND

Ischemic heart disease (IHD) is linked to brain white matter (WM) breakdown but how age or disease effects WM integrity, and whether it is reversible using cardiac rehabilitation (CR), remains unclear.

PURPOSE

To assess the effects of brain aging, cardiovascular disease, and CR on WM microstructure in brains of IHD patients following a cardiac event.

STUDY TYPE

Retrospective.

POPULATION

Thirty-five IHD patients (9 females; mean age = 59 ± 8 years), 21 age-matched healthy controls (10 females; mean age = 59 ± 8 years), and 25 younger controls (14 females; mean age = 26 ± 4 years).

FIELD STRENGTH/SEQUENCE

3 T diffusion-weighted imaging with single-shot echo planar imaging acquired at 3 months and 9 months post-cardiac event.

ASSESSMENT

Tract-based spatial statistics (TBSS) and tractometry were used to compare fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in cerebral WM between: 1) older and younger controls to distinguish age-related from disease-related WM changes; 2) IHD patients at baseline (pre-CR) and age-matched controls to investigate if cardiovascular disease exacerbates age-related WM changes; and 3) IHD patients pre-CR and post-CR to investigate the neuroplastic effect of CR on WM microstructure.

STATISTICAL TESTS

Two-sample unpaired t-test (age: older vs. younger controls; IHD: IHD pre-CR vs. age-matched controls). One-sample paired t-test (CR: IHD pre- vs. post-CR). Statistical threshold: P < 0.05 (FWE-corrected).

RESULTS

TBSS and tractometry revealed widespread WM changes in older controls compared to younger controls while WM clusters of decreased FA in the fornix and increased MD in body of corpus callosum were observed in IHD patients pre-CR compared to age-matched controls. Robust WM improvements (increased FA, increased AD) were observed in IHD patients post-CR.

DATA CONCLUSION

In IHD, both brain aging and cardiovascular disease may contribute to WM disruptions. IHD-related WM disruptions may be favorably modified by CR.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Antidepressant-related microstructural changes in the external capsule

Several magnetic resonance imaging (MRI) studies have reported that antidepressant medications are strongly linked to brain microstructural alterations. Notably, external capsule alterations have been reported to be a biological marker for therapeutic response. However, prior studies did not investigate whether a change in the neurite density or directional coherence of white matter (WM) fibers underlies the observed microstructural alterations. This MRI-based case-control study examined the relationship between patients' current use of antidepressant medications and advanced measurements of external capsule WM microstructure derived from multishell diffusion imaging using neurite orientation dispersion and density imaging (NODDI). The study compared a group of thirty-five participants who were taking antidepressant medications comprising selective serotonin reuptake inhibitors (SSRIs) (n = 25) and serotonin and norepinephrine reuptake inhibitors (SNRIs) with a control group of thirty-five individuals matched in terms of age, sex, race, and atherosclerotic cardiovascular risk factors. All participants were selected from the Dallas Heart Study phase 2, a multi-ethnic, population-based cohort study. A series of multiple linear regression analyses were conducted to predict microstructural characteristics of the bilateral external capsule using age, sex, and antidepressant medications as predictor variables. There was significantly reduced neurite density in the bilateral external capsules of patients taking SSRIs. Increased orientation dispersion in the external capsule was predominantly seen in patients taking SNRIs. Our findings suggest an association between specific external capsule microstructural changes and antidepressant medications, including reduced neurite density for SSRIs and increased orientation dispersion for SNRIs.

Brain elastography in aging relates to fluid/solid trendlines

The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury. We address these issues by examining trendlines in aging from our elastography data, also utilizing data from an earlier landmark study of brain composition, and from a biophysics model that captures the multiscale biphasic (fluid/solid) structure of the brain. Taken together, these imply that long term changes in extracellular water in the glymphatic system of the brain along with a decline in the extracellular matrix have a profound effect on the measured viscoelastic properties. Specifically, the trendlines indicate that water tends to replace solid fraction as a function of age, then grey matter stiffness decreases inversely as water fraction squared, whereas white matter stiffness declines inversely as water fraction to the 2/3 power, a behavior consistent with the cylindrical shape of the axons. These unique behaviors point to elastography of the brain as an important macroscopic measure of underlying microscopic structural change, with direct implications for clinical studies of aging, disease, and injury.

Life-course neighbourhood deprivation and brain structure in older adults: the Lothian Birth Cohort 1936

Neighbourhood disadvantage may be associated with brain health but the importance of exposure at different stages of the life course is poorly understood. Utilising the Lothian Birth Cohort 1936, we explored the relationship between residential neighbourhood deprivation from birth to late adulthood, and global and local neuroimaging measures at age 73. A total of 689 participants had at least one valid brain measures (53% male); to maximise the sample size structural equation models with full information maximum likelihood were conducted. Residing in disadvantaged neighbourhoods in mid- to late adulthood was associated with smaller total brain (β = -0.06; SE = 0.02; sample size[N] = 658; number of pairwise complete observations[n]=390), grey matter (β = -0.11; SE = 0.03; N = 658; n = 390), and normal-appearing white matter volumes (β = -0.07; SE = 0.03; N = 658; n = 390), thinner cortex (β = -0.14; SE = 0.06; N = 636; n = 379), and lower general white matter fractional anisotropy (β = -0.19; SE = 0.06; N = 665; n = 388). We also found some evidence on the accumulating impact of neighbourhood deprivation from birth to late adulthood on age 73 total brain (β = -0.06; SE = 0.02; N = 658; n = 276) and grey matter volumes (β = -0.10; SE = 0.04; N = 658; n = 276). Local analysis identified affected focal cortical areas and specific white matter tracts. Among individuals belonging to lower social classes, the brain-neighbourhood associations were particularly strong, with the impact of neighbourhood deprivation on total brain and grey matter volumes, and general white matter fractional anisotropy accumulating across the life course. Our findings suggest that living in deprived neighbourhoods across the life course, but especially in mid- to late adulthood, is associated with adverse brain morphologies, with lower social class amplifying the vulnerability.

Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure

Biological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes. Diffusion MRI is an important in vivo, non-invasive methodology that provides a window into brain tissue microstructure. Our study develops multiple end-to-end classification models that accurately estimates the sex of a subject using volumetric diffusion MRI data and uses these models to identify white matter regions that differ the most between men and women. 471 male and 560 female healthy subjects (age range, 22-37 years) from the Human Connectome Project are included. Fractional anisotropy, mean diffusivity and mean kurtosis are used to capture brain tissue microstructure characteristics. Diffusion parametric maps are registered to a standard template to reduce bias that can arise from macroscopic anatomical differences like brain size and contour. This study employ three major model architectures: 2D convolutional neural networks, 3D convolutional neural networks and Vision Transformer (with self-supervised pretraining). Our results show that all 3 models achieve high sex classification performance (test AUC 0.92-0.98) across all diffusion metrics indicating definitive differences in white matter tissue microstructure between males and females. We further use complementary model architectures to inform about the pattern of detected microstructural differences and the influence of short-range versus long-range interactions. Occlusion analysis together with Wilcoxon signed-rank test is used to determine which white matter regions contribute most to sex classification. The results indicate that sex-related differences manifest in both local features as well as global features / longer-distance interactions of tissue microstructure. Our highly consistent findings across models provides new insight supporting differences between male and female brain cellular-level tissue organization particularly in the central white matter.

Spatiotemporal Patterns of White Matter Maturation after Pre-Adolescence: A Diffusion Kurtosis Imaging Study

Diffusion tensor imaging (DTI) enables the assessment of changes in brain tissue microstructure during maturation and ageing. In general, patterns of cerebral maturation and decline render non-monotonic lifespan trajectories of DTI metrics with age, and, importantly, the rate of microstructural changes is heterochronous for various white matter fibres. Recent studies have demonstrated that diffusion kurtosis imaging (DKI) metrics are more sensitive to microstructural changes during ageing compared to those of DTI. In a previous work, we demonstrated that the Cohen's d of mean diffusional kurtosis (dMK) represents a useful biomarker for quantifying maturation heterochronicity. However, some inferences on the maturation grades of different fibre types, such as association, projection, and commissural, were of a preliminary nature due to the insufficient number of fibres considered. Hence, the purpose of this follow-up work was to further explore the heterochronicity of microstructural maturation between pre-adolescence and middle adulthood based on DTI and DKI metrics. Using the effect size of the between-group parametric changes and Cohen's d, we observed that all commissural fibres achieved the highest level of maturity, followed by the majority of projection fibres, while the majority of association fibres were the least matured. We also demonstrated that dMK strongly correlates with the maxima or minima of the lifespan curves of DTI metrics. Furthermore, our results provide substantial evidence for the existence of spatial gradients in the timing of white matter maturation. In conclusion, our data suggest that DKI provides useful biomarkers for the investigation of maturation spatial heterogeneity and heterochronicity.

Finding the Words: How Does the Aging Brain Process Language? A Focused Review of Brain Connectivity and Compensatory Pathways

As people age, there is a natural decline in cognitive functioning and brain structure. However, the relationship between brain function and cognition in older adults is neither straightforward nor uniform. Instead, it is complex, influenced by multiple factors, and can vary considerably from one person to another. Reserve, compensation, and maintenance mechanisms may help explain why some older adults can maintain high levels of performance while others struggle. These mechanisms are often studied concerning memory and executive functions that are particularly sensitive to the effects of aging. However, language abilities can also be affected by age, with changes in production fluency. The impact of brain changes on language abilities needs to be further investigated to understand the dynamics and patterns of aging, especially successful aging. We previously modeled several compensatory profiles of language production and lexical access/retrieval in aging within the Lexical Access and Retrieval in Aging (LARA) model. In the present paper, we propose an extended version of the LARA model, called LARA-Connectivity (LARA-C), incorporating recent evidence on brain connectivity. Finally, we discuss factors that may influence the strategies implemented with aging. The LARA-C model can serve as a framework to understand individual performance and open avenues for possible personalized interventions.

Physiological aging and inflammation-induced cellular senescence may contribute to oligodendroglial dysfunction in MS

Aging affects all cell types in the CNS and plays an important role in CNS diseases. However, the underlying molecular mechanisms driving these age-associated changes and their contribution to diseases are only poorly understood. The white matter in the aging brain as well as in diseases, such as Multiple sclerosis is characterized by subtle abnormalities in myelin sheaths and paranodes, suggesting that oligodendrocytes, the myelin-maintaining cells of the CNS, lose the capacity to preserve a proper myelin structure and potentially function in age and certain diseases. Here, we made use of directly converted oligodendrocytes (dchiOL) from young, adult and old human donors to study age-associated changes. dchiOL from all three age groups differentiated in an comparable manner into O4 + immature oligodendrocytes, but the proportion of MBP + mature dchiOL decreased with increasing donor age. This was associated with an increased ROS production and upregulation of cellular senescence markers such as CDKN1A, CDKN2A in old dchiOL. Comparison of the transcriptomic profiles of dchiOL from adult and old donors revealed 1324 differentially regulated genes with limited overlap with transcriptomic profiles of the donors' fibroblasts or published data sets from directly converted human neurons or primary rodent oligodendroglial lineage cells. Methylome analyses of dchiOL and human white matter tissue samples demonstrate that chronological and epigenetic age correlate in CNS white matter as well as in dchiOL and resulted in the identification of an age-specific epigenetic signature. Furthermore, we observed an accelerated epigenetic aging of the myelinated, normal appearing white matter of multiple sclerosis (MS) patients compared to healthy individuals. Impaired differentiation and upregulation of cellular senescence markers could be induced in young dchiOL in vitro using supernatants from pro-inflammatory microglia. In summary, our data suggest that physiological aging as well as inflammation-induced cellular senescence contribute to oligodendroglial pathology in inflammatory demyelinating diseases such as MS.

Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models

Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.

The Neurobiology of Life Course Socioeconomic Conditions and Associated Cognitive Performance in Middle to Late Adulthood

Despite major advances, our understanding of the neurobiology of life course socioeconomic conditions is still scarce. This study aimed to provide insight into the pathways linking socioeconomic exposures-household income, last known occupational position, and life course socioeconomic trajectories-with brain microstructure and cognitive performance in middle to late adulthood. We assessed socioeconomic conditions alongside quantitative relaxometry and diffusion-weighted magnetic resonance imaging indicators of brain tissue microstructure and cognitive performance in a sample of community-dwelling men and women (N = 751, aged 50-91 years). We adjusted the applied regression analyses and structural equation models for the linear and nonlinear effects of age, sex, education, cardiovascular risk factors, and the presence of depression, anxiety, and substance use disorders. Individuals from lower-income households showed signs of advanced brain white matter (WM) aging with greater mean diffusivity (MD), lower neurite density, lower myelination, and lower iron content. The association between household income and MD was mediated by neurite density (B = 0.084, p = 0.003) and myelination (B = 0.019, p = 0.009); MD partially mediated the association between household income and cognitive performance (B = 0.017, p < 0.05). Household income moderated the relation between WM microstructure and cognitive performance, such that greater MD, lower myelination, or lower neurite density was only associated with poorer cognitive performance among individuals from lower-income households. Individuals from higher-income households showed preserved cognitive performance even with greater MD, lower myelination, or lower neurite density. These findings provide novel mechanistic insights into the associations between socioeconomic conditions, brain anatomy, and cognitive performance in middle to late adulthood.

The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials

Schizophrenia is a significant worldwide health concern, affecting over 20 million individuals and contributing to a potential reduction in life expectancy by up to 14.5 years. Despite its profound impact, the precise pathological mechanisms underlying schizophrenia continue to remain enigmatic, with previous research yielding diverse and occasionally conflicting findings. Nonetheless, one consistently observed phenomenon in brain imaging studies of schizophrenia patients is the disruption of white matter, the bundles of myelinated axons that provide connectivity and rapid signalling between brain regions. Myelin is produced by specialised glial cells known as oligodendrocytes, which have been shown to be disrupted in post-mortem analyses of schizophrenia patients. Oligodendrocytes are generated throughout life by a major population of oligodendrocyte progenitor cells (OPC), which are essential for white matter health and plasticity. Notably, a decline in a specific subpopulation of OPC has been identified as a principal factor in oligodendrocyte disruption and white matter loss in the aging brain, suggesting this may also be a factor in schizophrenia. In this review, we analysed genomic databases to pinpoint intersections between aging and schizophrenia and identify shared mechanisms of white matter disruption and cognitive dysfunction.

Alterations of the cerebral microstructure in patients with noise-induced hearing loss: A diffusion tensor imaging study

OBJECTIVE

To explore the changes in the cerebral microstructure of patients with noise-induced hearing loss (NIHL) using diffusion tensor imaging (DTI).

METHOD

Overall, 122 patients with NIHL (mild [MP, n = 79], relatively severe patients [including moderate and severe; RSP, n = 32], and undetermined [lost to follow-up, n = 11]) and 84 healthy controls (HCs) were enrolled. All clinical data, including age, education level, hearing threshold, occupation type, noise exposure time, and some scale scores (including the Mini-Mental State Examination [MMSE], tinnitus handicap inventory [THI], and Hamilton Anxiety Scale [HAMA]), were collected and analyzed. All participants underwent T1WI3DFSPGR and DTI, and tract-based spatial statistics and region of interest (ROI) analysis were used for assessment.

RESULTS

The final sample included 71 MP, 28 RSP, and 75 HCs. The HAMA scores of the three groups were significantly different (p < .05). The noise exposure times, hearing thresholds, and HAMA scores of the MP and RSP were significantly different (p < .05). The noise exposure time was positively correlated with the hearing threshold and negatively correlated with the HAMA scores (p < .05), whereas the THI scores were positively correlated with the hearing threshold (p < .05). DTI analysis showed that all DTI parameters (fractional anisotropy [FA], axial diffusivity [AD], mean diffusivity [MD], and radial diffusivity [RD]) were significantly different in the left inferior longitudinal fasciculus (ILF) and left inferior fronto-occipital fasciculus (IFOF) for the three groups (p < .05). In addition, the FA values were significantly lower in the bilateral corticospinal tract (CST), right fronto-pontine tract (FPT), right forceps major, left superior longitudinal fasciculus (temporal part) (SLF), and left cingulum (hippocampus) (C-H) of the MP and RSP than in those of the HCs (p < .05); the AD values showed diverse changes in the bilateral CST, left IFOF, right anterior thalamic radiation, right external capsule (EC), right SLF, and right superior cerebellar peduncle (SCP) of the MP and RSP relative to those of the HC (p < .05). However, there were no significant differences among the bilateral auditory cortex ROIs of the three groups (p > .05). There was a significant negative correlation between the FA and HAMA scores for the left IFOF/ILF, right FPT, left SLF, and left C-H for the three groups (p < .05). There was a significant positive correlation between the AD and HAMA scores for the left IFOF/ILF and right EC of the three groups (p < .05). There were significantly positive correlations between the RD/MD and HAMA scores in the left IFOF/ILF of the three groups (p < .05). There was a significant negative correlation between the AD in the right SCP and noise exposure time of the MP and RSP groups (p < .05). The AD, MD, and RD in the left ROI were significantly positively correlated with hearing threshold in the MP and RSP groups (p < .05), whereas FA in the right ROI was significantly positively correlated with the HAMA scores for the three groups (p < .05).

CONCLUSION

The changes in the white matter (WM) microstructure may be related to hearing loss caused by noise exposure, and the WM structural abnormalities in patients with NIHL were mainly located in the syndesmotic fibers of the temporooccipital region, which affected the auditory and language pathways. This confirmed that the auditory pathways have abnormal structural connectivity in patients with NIHL.

Insights and improvements in correspondence between axonal volume fraction measured with diffusion-weighted MRI and electron microscopy

Biophysical diffusion-weighted imaging (DWI) models are increasingly used in neuroscience to estimate the axonal water fraction (f AW ), which in turn is key for noninvasive estimation of the axonal volume fraction (f A ). These models require thorough validation by comparison with a reference method, for example, electron microscopy (EM). While EM studies often neglect the unmyelinated axons and solely report the fraction of myelinated axons, in DWI both myelinated and unmyelinated axons contribute to the DWI signal. However, DWI models often include simplifications, for example, the neglect of differences in the compartmental relaxation times or fixed diffusivities, which in turn might affect the estimation off AW . We investigate whether linear calibration parameters (scaling and offset) can improve the comparability between EM- and DWI-based metrics off A . To this end, we (a) used six DWI models based on the so-called standard model of white matter (WM), including two models with fixed compartmental diffusivities (e.g., neurite orientation dispersion and density imaging, NODDI) and four models that fitted the compartmental diffusivities (e.g., white matter tract integrity, WMTI), and (b) used a multimodal data set including ex vivo diffusion DWI and EM data in mice with a broad dynamic range of fibre volume metrics. We demonstrated that the offset is associated with the volume fraction of unmyelinated axons and the scaling factor is associated with different compartmentalT 2 and can substantially enhance the comparability between EM- and DWI-based metrics off A . We found that DWI models that fitted compartmental diffusivities provided the most accurate estimates of the EM-basedf A . Finally, we introduced a more efficient hybrid calibration approach, where only the offset is estimated but the scaling is fixed to a theoretically predicted value. Using this approach, a similar one-to-one correspondence to EM was achieved for WMTI. The method presented can pave the way for use of validated DWI-based models in clinical research and neuroscience.

Cognitively healthy APOE4/4 carriers show white matter impairment associated with serum NfL and amyloid-PET

Except for aging, carrying the APOE ε4 allele (APOE4) is the most important risk factor for sporadic Alzheimer's disease. APOE4 carriers may have reduced capacity to recycle lipids, resulting in white matter microstructural abnormalities. In this study, we evaluated whether white matter impairment measured by diffusion tensor imaging (DTI) differs between healthy individuals with a different number of APOE4 alleles, and whether white matter impairment associates with brain beta-amyloid (Aβ) load and serum levels of neurofilament light chain (NfL). We studied 96 participants (APOE3/3, N = 37; APOE3/4, N = 39; APOE4/4, N = 20; mean age 70.7 (SD 5.22) years, 63% females) with a brain MRI including a DTI sequence (N = 96), Aβ-PET (N = 89) and a venous blood sample for the serum NfL concentration measurement (N = 88). Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AxD) in six a priori-selected white matter regions-of-interest (ROIs) were compared between the groups using ANCOVA, with sex and age as covariates. A voxel-weighted average of FA, MD, RD and AxD was calculated for each subject, and correlations with Aβ-PET and NfL levels were evaluated. APOE4/4 carriers exhibited a higher MD and a higher RD in the body of corpus callosum than APOE3/4 (p = 0.0053 and p = 0.0049, respectively) and APOE3/3 (p = 0.026 and p = 0.042). APOE4/4 carriers had a higher AxD than APOE3/4 (p = 0.012) and APOE3/3 (p = 0.040) in the right cingulum adjacent to cingulate cortex. In the total sample, composite MD, RD and AxD positively correlated with the cortical Aβ load (r = 0.26 to 0.33, p < 0.013 for all) and with serum NfL concentrations (r = 0.31 to 0.36, p < 0.0028 for all). In conclusion, increased local diffusivity was detected in cognitively unimpaired APOE4/4 homozygotes compared to APOE3/4 and APOE3/3 carriers, and increased diffusivity correlated with biomarkers of Alzheimer's disease and neurodegeneration. White matter impairment seems to be an early phenomenon in the Alzheimer's disease pathologic process in APOE4/4 homozygotes.

Magnetic Resonance Imaging Tissue Signatures Associated With White Matter Changes Due to Sporadic Cerebral Small Vessel Disease Indicate That White Matter Hyperintensities Can Regress

BACKGROUND

White matter hyperintensities (WMHs) might regress and progress contemporaneously, but we know little about underlying mechanisms. We examined WMH change and underlying quantitative magnetic resonance imaging tissue measures over 1 year in patients with minor ischemic stroke with sporadic cerebral small vessel disease.

METHODS AND RESULTS

We defined areas of stable normal-appearing white matter, stable WMHs, progressing and regressing WMHs based on baseline and 1-year brain magnetic resonance imaging. In these areas we assessed tissue characteristics with quantitative T1, fractional anisotropy (FA), mean diffusivity (MD), and neurite orientation dispersion and density imaging (baseline only). We compared tissue signatures cross-sectionally between areas, and longitudinally within each area. WMH change masks were available for N=197. Participants' mean age was 65.61 years (SD, 11.10), 59% had a lacunar infarct, and 68% were men. FA and MD were available for N=195, quantitative T1 for N=182, and neurite orientation dispersion and density imaging for N=174. Cross-sectionally, all 4 tissue classes differed for FA, MD, T1, and Neurite Density Index. Longitudinally, in regressing WMHs, FA increased with little change in MD and T1 (difference estimate, 0.011 [95% CI, 0.006-0.017]; -0.002 [95% CI, -0.008 to 0.003] and -0.003 [95% CI, -0.009 to 0.004]); in progressing and stable WMHs, FA decreased (-0.022 [95% CI, -0.027 to -0.017] and -0.009 [95% CI, -0.011 to -0.006]), whereas MD and T1 increased (progressing WMHs, 0.057 [95% CI, 0.050-0.063], 0.058 [95% CI, 0.050 -0.066]; stable WMHs, 0.054 [95% CI, 0.045-0.063], 0.049 [95% CI, 0.039-0.058]); and in stable normal-appearing white matter, MD increased (0.004 [95% CI, 0.003-0.005]), whereas FA and T1 slightly decreased and increased (-0.002 [95% CI, -0.004 to -0.000] and 0.005 [95% CI, 0.001-0.009]).

CONCLUSIONS

Quantitative magnetic resonance imaging shows that WMHs that regress have less abnormal microstructure at baseline than stable WMHs and follow trajectories indicating tissue improvement compared with stable and progressing WMHs.

"Pscore": A Novel Percentile-Based Metric to Accurately Assess Individual Deviations in Non-Gaussian Distributions of Quantitative MRI Metrics

BACKGROUND

Quantitative magnetic resonance imaging (MRI) metrics could be used in personalized medicine to assess individuals against normative distributions. Conventional Zscore analysis is inadequate in the presence of non-Gaussian distributions. Therefore, if quantitative MRI metrics deviate from normality, an alternative is needed.

PURPOSE

To confirm non-Gaussianity of diffusion MRI (dMRI) metrics on a publicly available dataset, and to propose a novel percentile-based method, "Pscore" to address this issue.

STUDY TYPE

Retrospective cohort.

POPULATION

Nine hundred and sixty-one healthy young adults (age: 22-35 years, females: 53%) from the Human Connectome Project.

FIELD STRENGTH/SEQUENCE

3-T, spin-echo diffusion echo-planar imaging, T1-weighted: MPRAGE.

ASSESSMENT

The dMRI data were preprocessed using the TORTOISE pipeline. Forty-eight regions of interest (ROIs) from the JHU atlas were redrawn on a study-specific diffusion tensor (DT) template and average values were computed from various DT and mean apparent propagator (MAP) metrics. For each ROI, percentile ranks across participants were computed to generate "Pscores"-which normalized the difference between the median and a participant's value with the corresponding difference between the median and the 5th/95th percentile values.

STATISTICAL TESTS

ROI-wise distributions were assessed using log transformations, Zscore, and the "Pscore" methods. The percentages of extreme values above-95th and below-5th percentile boundaries (PEV>95 (%), PEV<5 (%)) were also assessed in the overall white matter. Bootstrapping was performed to test the reliability of Pscores in small samples (N = 100) using 100 iterations.

RESULTS

The dMRI metric distributions were systematically non-Gaussian, including positively skewed (eg, mean and radial diffusivity) and negatively skewed (eg, fractional and propagator anisotropy) metrics. This resulted in unbalanced tails in Zscore distributions (PEV>95  ≠ 5%, PEV<5  ≠ 5%) whereas "Pscore" distributions were symmetric and balanced (PEV>95  = PEV<5  = 5%); even for small bootstrapped samples (averagePEV > 95 ¯ = PEV < 5 ¯ = 5 ± 0 % $$ \overline{{\mathrm{PEV}}_{>95}}=\overline{{\mathrm{PEV}}_{<5}}=5\pm 0\% $$ [SD]).

DATA CONCLUSION

The inherent skewness observed for dMRI metrics may preclude the use of conventional Zscore analysis. The proposed "Pscore" method may help estimating individual deviations more accurately in skewed normative data, even from small datasets.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 1.

Association of Poor Oral Health With Neuroimaging Markers of White Matter Injury in Middle-Aged Participants in the UK Biobank

BACKGROUND AND OBJECTIVES

Poor oral health is a modifiable risk factor that is associated with clinically observed cardiovascular disease. However, the relationship between oral and brain health is not well understood. We tested the hypothesis that poor oral health is associated with worse neuroimaging brain health profiles in middle-aged persons without stroke or dementia.

METHODS

We performed a 2-stage cross-sectional neuroimaging study using UK Biobank data. First, we tested for association between self-reported poor oral health and MRI neuroimaging markers of brain health. Second, we used Mendelian randomization (MR) analyses to test for association between genetically determined poor oral health and the same neuroimaging markers. Poor oral health was defined as the presence of dentures or loose teeth. As instruments for the MR analysis, we used 116 independent DNA sequence variants linked to increased composite risk of dentures or teeth that are decayed, missing, or filled. Neuroimaging markers of brain health included white matter hyperintensity (WMH) volume and aggregate measures of fractional anisotropy (FA) and mean diffusivity (MD), 2 metrics indicative of white matter tract disintegrity obtained through diffusion tensor imaging across 48 brain regions.

RESULTS

We included 40,175 persons (mean age 55 years, female sex 53%) enrolled from 2006 to 2010, who underwent a dedicated research brain MRI between 2014 and 2016. Among participants, 5,470 (14%) had poor oral health. Poor oral health was associated with a 9% increase in WMH volume (β = 0.09, SD = 0.014, p < 0.001), 10% change in aggregate FA score (β = 0.10, SD = 0.013, p < 0.001), and 5% change in aggregate MD score (β = 0.05, SD = 0.013, p < 0.001). Genetically determined poor oral health was associated with a 30% increase in WMH volume (β = 0.30, SD = 0.06, p < 0.001), 43% change in aggregate FA score (β = 0.43, SD = 0.06, p < 0.001), and 10% change in aggregate MD score (β = 0.10, SD = 0.03, p < 0.01).

DISCUSSION

Among middle age Britons without stroke or dementia, poor oral health was associated with worse neuroimaging brain health profiles. Genetic analyses confirmed these associations, supporting a potentially causal association. Because the neuroimaging markers evaluated in this study precede and are established risk factors of stroke and dementia, our results suggest that oral health, an easily modifiable process, may be a promising target for very early interventions focused on improving brain health.

Correlates of axonal content in healthy adult span: Age, sex, myelin, and metabolic health

As the emerging treatments that target grey matter pathology in Alzheimer's Disease have limited effectiveness, there is a critical need to identify new neural targets for treatments. White matter's (WM) metabolic vulnerability makes it a promising candidate for new interventions. This study examined the age and sex differences in estimates of axonal content, as well the associations of with highly prevalent modifiable health risk factors such as metabolic syndrome and adiposity. We estimated intra-axonal volume fraction (ICVF) using the Neurite Orientation Dispersion and Density Imaging (NODDI) in a sample of 89 cognitively and neurologically healthy adults (20-79 years). We showed that ICVF correlated positively with age and estimates of myelin content. The ICVF was also lower in women than men, across all ages, which difference was accounted for by intracranial volume. Finally, we found no association of metabolic risk or adiposity scores with the current estimates of ICVF. In addition, the previously observed adiposity-myelin associations (Burzynska et al., 2023) were independent of ICVF. Although our findings confirm the vulnerability of axons to aging, they suggest that metabolic dysfunction may selectively affect myelin content, at least in cognitively and neurologically healthy adults with low metabolic risk, and when using the specific MRI techniques. Future studies need to revisit our findings using larger samples and different MRI approaches, and identify modifiable factors that accelerate axonal deterioration as well as mechanisms linking peripheral metabolism with the health of myelin.

'Pscore' - A Novel Percentile-Based Metric to Accurately Assess Individual Deviations in Non-Gaussian Distributions of Quantitative MRI Metrics

BACKGROUND

Quantitative MRI metrics could be used in personalized medicine to assess individuals against normative distributions. Conventional Zscore analysis is inadequate in the presence of non-Gaussian distributions. Therefore, if quantitative MRI metrics deviate from normality, an alternative is needed.

PURPOSE

To confirm non-Gaussianity of diffusion MRI (dMRI) metrics on a publicly available dataset, and to propose a novel percentile-based method, 'Pscore' to address this issue.

STUDY TYPE

Retrospective cohort.

POPULATION

961 healthy young-adults (age:22-35 years, Females:53%) from the Human Connectome Project.

FIELD STRENGTH/SEQUENCE

3-T, spin-echo diffusion echo-planar imaging, T1-weighted: MPRAGE.

ASSESSMENT

The dMRI data were preprocessed using the TORTOISE pipeline. Forty-eight regions of interest (ROIs) from the JHU-atlas were redrawn on a study-specific diffusion tensor (DT) template and average values were computed from various DT and mean apparent propagator (MAP) metrics. For each ROI, percentile ranks across participants were computed to generate 'Pscores'- which normalized the difference between the median and a participant's value with the corresponding difference between the median and the 5th/95th percentile values.

STATISTICAL TESTS

ROI-wise distributions were assessed using Log transformations, Zscore, and the 'Pscore' methods. The percentages of extreme values above-95th and below-5th percentile boundaries (PEV < 5 ( % ) ,PEV < 5 ( % ) ) were also assessed in the overall white matter. Bootstrapping was performed to test the reliability of Pscores in small samples (n=100) using 100 iterations.

RESULTS

The dMRI metric distributions were systematically non-Gaussian, including positively skewed (e.g., mean and radial distributions P E V > 95 ≠ 5 % , P E V < 5 ≠ 5 % whereas 'Pscore' distributions were symmetric and balanced P E V > 95 = P E V < 5 = 5 % ; even for small bootstrapped samples (average P E V > 95 ¯ = P E V < 5 ¯ = 5 ± 0 % S D ).

DATA CONCLUSION

The inherent skewness observed for dMRI metrics may preclude the use of conventional Zscore analysis. The proposed 'Pscore' method may help estimating individual deviations more accurately in skewed normative data, even from small datasets.

Current Auditory Hallucinations Are Not Associated With Specific White Matter Diffusion Alterations in Schizophrenia

Background and Hypothesis

Studies have linked auditory hallucinations (AH) in schizophrenia spectrum disorders (SCZ) to altered cerebral white matter microstructure within the language and auditory processing circuitry (LAPC). However, the specificity to the LAPC remains unclear. Here, we investigated the relationship between AH and DTI among patients with SCZ using diffusion tensor imaging (DTI).

Study Design

We included patients with SCZ with (AH+; n = 59) and without (AH-; n = 81) current AH, and 140 age- and sex-matched controls. Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were extracted from 39 fiber tracts. We used principal component analysis (PCA) to identify general factors of variation across fiber tracts and DTI metrics. Regression models adjusted for sex, age, and age2 were used to compare tract-wise DTI metrics and PCA factors between AH+, AH-, and healthy controls and to assess associations with clinical characteristics.

Study Results

Widespread differences relative to controls were observed for MD and RD in patients without current AH. Only limited differences in 2 fiber tracts were observed between AH+ and controls. Unimodal PCA factors based on MD, RD, and AD, as well as multimodal PCA factors, differed significantly relative to controls for AH-, but not AH+. We did not find any significant associations between PCA factors and clinical characteristics.

Conclusions

Contrary to previous studies, DTI metrics differed mainly in patients without current AH compared to controls, indicating a widespread neuroanatomical distribution. This challenges the notion that altered DTI metrics within the LAPC is a specific feature underlying AH.

Frontoparietal function and underlying structure reflect capacity for motor skill acquisition during healthy aging

While capacity for motor skill acquisition changes with healthy aging, there has been little consideration of how age-related changes in brain function or baseline brain structure support motor skill acquisition. We examined: (1) age-dependent changes in functional reorganization related to frontoparietal regions during motor skill acquisition, and (2) whether capacity for motor skill acquisition relates to baseline white matter microstructure in frontoparietal tracts. Healthy older and younger adults engaged in 4 weeks of skilled motor practice. Resting-state functional connectivity (rsFC) assessed functional reorganization before and after practice. Diffusion tensor imaging indexed microstructure of a frontoparietal tract at baseline, generated by rsFC seeds. Motor skill acquisition was associated with decreases in rsFC in healthy older adults and increases in rsFC in healthy younger adults. Frontoparietal tract microstructure was lower in healthy older versus younger adults, yet it was negatively associated with rate of skill acquisition regardless of group. Findings indicate that age-dependent alterations in frontoparietal function and baseline structure of a frontoparietal tract reflect capacity for motor skill acquisition.

Vascular risk factors, white matter microstructure, and depressive symptoms: a longitudinal analysis in the UK Biobank

BACKGROUND

Cumulative burden from vascular risk factors (VRFs) has been associated with an increased risk of depressive symptoms in mid- and later life. It has been hypothesised that this association arises because VRFs disconnect fronto-subcortical white matter tracts involved in mood regulation, which puts older adults at higher risk of developing depressive symptoms. However, evidence for the hypothesis that disconnection of white matter tracts underlies the association between VRF burden and depressive symptoms from longitudinal studies is scarce.

METHODS

This preregistered study analysed longitudinal data from 6,964 middle-aged and older adults from the UK Biobank who participated in consecutive assessments of VRFs, brain imaging, and depressive symptoms. Using mediation modelling, we directly tested to what extend white matter microstructure mediates the longitudinal association between VRF burden and depressive symptoms.

RESULTS

VRF burden showed a small association with depressive symptoms at follow-up. However, there was no evidence that fractional anisotropy (FA) of white matter tracts mediated this association. Additional analyses also yielded no mediating effects using alternative operationalisations of VRF burden, mean diffusivity (MD) of single tracts, or overall average of tract-based white matter microstructure (global FA, global MD, white matter hyperintensity volume).

CONCLUSIONS

Our results lend no support to the hypothesis that disconnection of white matter tracts underlies the association between VRF burden and depressive symptoms, while highlighting the relevance of using longitudinal data to directly test pathways linking vascular and mental health.

Associations between white matter integrity of the cingulum bundle, surrounding gray matter regions, and cognition across the dementia continuum

INTRODUCTION

Previous Alzheimer's disease and related dementias (AD/ADRD) research studies have illustrated the significance of studying alterations in white matter (WM). Fewer studies have examined how WM integrity, measured with diffusion tensor imaging (DTI), is associated with volume of gray matter (GM) regions and measures of cognitive function in aged participants spanning the dementia continuum.

METHODS

Magnetic resonance imaging and cognitive data were collected from 241 Boston University Alzheimer's Disease Research Center participants who spanned from cognitively normal controls to amnestic mild cognitive impairment to having dementia. Primary DTI tracts of interest were the cingulum ventral (CV) and cingulum dorsal (CD) pathways. GM regions of interest (ROIs) were in the medial temporal lobe (MTL), prefrontal cortex, and retrosplenial cortex. Analyses of covariance models were used to assess differences in WM integrity across groups (control, amnestic mild cognitive impairment, and dementia). Multiple linear regression models were used to assess associations between WM integrity and GM volume, and with measures of memory and executive function.

RESULTS

Differences in WM integrity were shown in both cingulum pathways in participants across the dementia continuum. Associations between WM integrity of both cingulum pathways and volume of selected GM ROIs were widespread. Functionally significant associations were found between WM of the CV pathway and memory, independent of MTL GM volume.

DISCUSSION

Differences in WM integrity of the cingulum bundle and surrounding GM ROI are likely related to the progression of AD/ADRD. Such differences should continue to be studied, particularly in association with memory performance.

3DCNN predicting brain age using diffusion tensor imaging

Neuroimaging-based brain age prediction using deep learning is gaining popularity. However, few studies have attempted to leverage diffusion tensor imaging (DTI) to predict brain age. In this study, we proposed a 3D convolutional neural network model (3DCNN) and trained it on fractional anisotropy (FA) data from six publicly available datasets (n = 2406, age = 17-60) to estimate brain age. Implementing a two-loop nested cross-validation scheme with a tenfold cross-validation procedure, we achieved a robust prediction performance of a mean absolute error (MAE) of 2.785 and a correlation coefficient of 0.932. We also employed Grad-Cam++ to visualize the salient features of the proposed model. We identified a few highly salient fiber tracts, including the genu of corpus callosum and the left cerebellar peduncle, among others that play a pivotal role in our model. In sum, our model reliably predicted brain age and provided novel insight into age-related changes in brains' axonal structure.

Exploring Successful Cognitive Aging: Insights Regarding Brain Structure, Function, and Demographics

In the realm of cognitive science, the phenomenon of "successful cognitive aging" stands as a hallmark of individuals who exhibit cognitive abilities surpassing those of their age-matched counterparts. However, it is paramount to underscore a significant gap in the current research, which is marked by a paucity of comprehensive inquiries that deploy substantial sample sizes to methodically investigate the cerebral biomarkers and contributory elements underpinning this cognitive success. It is within this context that our present study emerges, harnessing data derived from the UK Biobank. In this study, a highly selective cohort of 1060 individuals aged 65 and above was meticulously curated from a larger pool of 17,072 subjects. The selection process was guided by their striking cognitive resilience, ascertained via rigorous evaluation encompassing both generic and specific cognitive assessments, compared to their peers within the same age stratum. Notably, the cognitive abilities of the chosen participants closely aligned with the cognitive acumen commonly observed in middle-aged individuals. Our study leveraged a comprehensive array of neuroimaging-derived metrics, obtained from three Tesla MRI scans (T1-weighted images, dMRI, and resting-state fMRI). The metrics included image-derived phenotypes (IDPs) that addressed grey matter morphology, the strength of brain network connectivity, and the microstructural attributes of white matter. Statistical analyses were performed employing ANOVA, Mann-Whitney U tests, and chi-square tests to evaluate the distinctive aspects of IDPs pertinent to the domain of successful cognitive aging. Furthermore, these analyses aimed to elucidate lifestyle practices that potentially underpin the maintenance of cognitive acumen throughout the aging process. Our findings unveiled a robust and compelling association between heightened cognitive aptitude and the integrity of white matter structures within the brain. Furthermore, individuals who exhibited successful cognitive aging demonstrated markedly enhanced activity in the cerebral regions responsible for auditory perception, voluntary motor control, memory retention, and emotional regulation. These advantageous cognitive attributes were mirrored in the health-related lifestyle choices of the surveyed cohort, characterized by elevated educational attainment, a lower incidence of smoking, and a penchant for moderate alcohol consumption. Moreover, they displayed superior grip strength and enhanced walking speeds. Collectively, these findings furnish valuable insights into the multifaceted determinants of successful cognitive aging, encompassing both neurobiological constituents and lifestyle practices. Such comprehensive comprehension significantly contributes to the broader discourse on aging, thereby establishing a solid foundation for the formulation of targeted interventions aimed at fostering cognitive well-being among aging populations.

APOE4 allele-specific associations between diet, multimodal biomarkers, and cognition among Puerto Rican adults in Massachusetts

Background

Apolipoprotein E (APOE) is the strongest genetic risk factor for sporadic Alzheimer's Disease (AD), and the ε4 allele (APOE4) may interact with lifestyle factors that relate to brain structural changes, underlying the increased risk of AD. However, the exact role of APOE4 in mediating interactions between the peripheral circulatory system and the central nervous system, and how it may link to brain and cognitive aging requires further elucidation. In this analysis, we investigated the association between APOE4 carrier status and multimodal biomarkers (diet, blood markers, clinical diagnosis, brain structure, and cognition) in the context of gene-environment interactions.

Methods

Participants were older adults from a longitudinal observational study, the Boston Puerto Rican Health Study (BPRHS), who self-identified as of Puerto Rican descent. Demographics, APOE genotype, diet, blood, and clinical data were collected at baseline and at approximately 12th year, with the addition of multimodal brain magnetic resonance imaging (MRI) (T1-weighted and diffusion) and cognitive testing acquired at 12-year. Measures were compared between APOE4 carriers and non-carriers, and associations between multimodal variables were examined using correlation and multivariate network analyses within each group.

Results

A total of 156 BPRHS participants (mean age at imaging = 68 years, 77% female, mean follow-up 12.7 years) with complete multimodal data were included in the current analysis. APOE4 carriers (n = 43) showed reduced medial temporal lobe (MTL) white matter (WM) microstructural integrity and lower mini-mental state examination (MMSE) score than non-carriers (n = 113). This pattern was consistent with an independent sample from the Alzheimer's Disease Neuroimaging Initiative (ADNI) of n = 283 non-Hispanic White adults without dementia (mean age = 75, 40% female). Within BPRHS, carriers showed distinct connectivity patterns between multimodal biomarkers, characterized by stronger direct network connections between baseline diet/blood markers with 12-year blood/clinical measures, and between blood markers (especially lipids and cytokines) and WM. Cardiovascular burden (i.e., hypertension and diabetes status) was associated with WM integrity for both carriers and non-carriers.

Conclusion

APOE4 carrier status affects interactions between dietary factors, multimodal blood biomarkers, and MTL WM integrity across ~12 years of follow-up, which may reflect increased peripheral-central systems crosstalk following blood-brain barrier breakdown in carriers.

High resolution 0.5mm isotropic T1-weighted and diffusion tensor templates of the brain of non-demented older adults in a common space for the MIITRA atlas

High quality, high resolution T1-weighted (T1w) and diffusion tensor imaging (DTI) brain templates located in a common space can enhance the sensitivity and precision of template-based neuroimaging studies. However, such multimodal templates have not been constructed for the older adult brain. The purpose of this work which is part of the MIITRA atlas project was twofold: (A) to develop 0.5 mm isotropic resolution T1w and DTI templates that are representative of the brain of non-demented older adults and are located in the same space, using advanced multimodal template construction techniques and principles of super resolution on data from a large, diverse, community cohort of 400 non-demented older adults, and (B) to systematically compare the new templates to other standardized templates. It was demonstrated that the new MIITRA-0.5mm T1w and DTI templates are well-matched in space, exhibit good definition of brain structures, including fine structures, exhibit higher image sharpness than other standardized templates, and are free of artifacts. The MIITRA-0.5mm T1w and DTI templates allowed higher intra-modality inter-subject spatial normalization precision as well as higher inter-modality intra-subject spatial matching of older adult T1w and DTI data compared to other available templates. Consequently, MIITRA-0.5mm templates allowed detection of smaller inter-group differences for older adult data compared to other templates. The MIITRA-0.5mm templates were also shown to be most representative of the brain of non-demented older adults compared to other templates with submillimeter resolution. The new templates constructed in this work constitute two of the final products of the MIITRA atlas project and are anticipated to have important implications for the sensitivity and precision of studies on older adults.