Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease.

Estimated brain age from magnetic resonance image (MRI) and its deviation from chronological age can provide early insights into potential neurodegenerative diseases, supporting early detection and implementation of prevention strategies to slow disease progression and onset. Diffusion MRI (dMRI), a widely used modality for brain age estimation, presents an opportunity to build an earlier biomarker for neurodegenerative disease prediction because it captures subtle microstructural changes that precede more perceptible macrostructural changes. However, the coexistence of macro- and micro-structural information in dMRI raises the question of whether current dMRI-based brain age estimation models are leveraging the intended microstructural information or if they inadvertently rely on the macrostructural information.

Tractography from T1-weighted MRI: Empirically exploring the clinical viability of streamline propagation without diffusion MRI.

Over the last few decades, diffusion MRI (dMRI) streamline tractography has emerged as the dominant method forestimation of white matter (WM) pathways in the brain. One key limitation to this technique is that modern tractography implementations require high angular resolution diffusion imaging (HARDI). However, HARDI can be difficult to collect clinically, limiting the reach of tractography analyses to research cohorts and thus limiting many WM investigations to certain populations and pathologies.

Advancing Fair and Explainable Machine Learning for Neuroimaging Dementia Pattern Classification in Multi-Ethnic Populations.

Dementia, a degenerative disease affecting millions globally, is projected to triple by 2050. Early and precise diagnosis is essential for effective treatment and improved quality of life. However, current diagnostic approaches frequently demonstrate inconsistent precision and impartiality, particularly among diverse cultural groups.

White Matter Abnormalities and Cognition in Aging and Alzheimer Disease.

Importance: There has yet to be a large-scale study quantifying the association between white matter microstructure and cognitive performance and decline in aging and Alzheimer disease (AD).

Objective: To investigate the associations between tract-specific white matter microstructure and cognitive performance and decline in aging and AD-related cognitive impairment.

Design Setting And Participants: This prognostic study of aging and AD, a secondary data analysis of multisite cohort studies, acquired data from 9 cohorts between September 2002 and November 2022.

Sex-Specific Genetic Drivers of Memory, Executive Functioning, and Language Performance in Older Adults.

We previously identified sex-specific genetic loci associated with memory performance, a strong Alzheimer's disease (AD) endophenotype. Here, we expand on this work by conducting sex-specific, cross-ancestral, genome-wide meta-analyses of three cognitive domains (memory, executive functioning, and language) in 33,918 older adults (57% female; 41% cognitively impaired; mean age=73 years) from 10 aging and AD cohorts. All three domains were comparably heritable across sexes.

Genetic architecture of the limbic white matter microstructure in aging and Alzheimer's Disease.

Background: Limbic white matter (WM) abnormalities are prevalent in aging and Alzheimer's disease (AD), yet their underlying biological mechanisms remain unclear. This study aims to identify the genetic architecture of limbic WM microstructure in older adults by leveraging harmonized data from multiple cohorts, including those enriched for cognitively impaired individuals.

Methods: We analyzed diffusion MRI (dMRI) data from 2,614 non-Hispanic White older adults (mean age = 73.

Harmonized connectome resampling for variance in voxel sizes.

Diffusion MRI (dMRI) fiber tractography presents exciting opportunities to deepen our knowledge of human brain connectivity and discover novel alterations in white matter. To date, there has been no comprehensive study characterizing the effect of dMRI voxel resolution on the resulting connectome for subject data. We assessed the statistical significance of graph measures derived from dMRI data by comparing connectomes from the same scans across different resolutions with 44 subjects (32 female) from the Human Connectome Project - Young Adult dataset (HCP-YA) with scan/rescan data (88 scans).

Cerebrospinal fluid YKL-40 relates to white matter hyperintensity progression in females but not males over a 6-year period.

Introduction: Neuroinflammation may have sex-specific effects on white matter injury and impact the development of dementia.

Methods: Human chitinase-3-like protein-1 (YKL-40) concentrations at baseline were related to white matter hyperintensity (WMH) volume, free water (FW), and FW-corrected fractional anisotropy using linear effects models (for cross-sectional outcomes) and linear mixed-effects models (for longitudinal outcomes), adjusting for demographic and medical risk factors. Models were repeated with a sex-interaction term and then stratified by sex.

The effect of Alzheimer's disease genetic factors on limbic white matter microstructure.

Introduction: White matter (WM) microstructure is essential for brain function but deteriorates with age and in neurodegenerative conditions such as Alzheimer's disease (AD). Diffusion MRI, enhanced by advanced bi-tensor models accounting for free water (FW), enables in vivo quantification of WM microstructural differences.

Methods: To evaluate how AD genetic risk factors affect limbic WM microstructure - crucial for memory and early impacted in disease - we conducted linear regression analyses in a cohort of 2,614 non-Hispanic White aging adults (aged 50.

Associations between haplotypes and limbic system white matter microstructure.

Introduction: We assessed associations between apolipoprotein E Translocase of Outer Mitochondrial Membrane 40 (-'523 haplotypes and white matter microstructure (WMM) across limbic tracts important for memory and cognition in non-Hispanic Black and White individuals.

Methods: Linear regression models, stratified by and racialized groups, assessed associations between -'523-S and limbic tract WMM free-water (FW) and free-water-corrected fractional anisotropy (FAFWcorr).

Results: Black-ε4+-one-'523-S carriers had lower FW in the cingulum and inferior longitudinal fasciculus compared to Black-ε4+-no-'523-S carriers.

Novel modelling approaches to elucidate the genetic architecture of resilience to Alzheimer's disease.

Up to 30% of older adults meet pathological criteria for a diagnosis of Alzheimer's disease at autopsy yet never show signs of cognitive impairment. Recent work has highlighted genetic drivers of this resilience, or better-than-expected cognitive performance given a level of neuropathology, that allow the aged brain to protect itself from the downstream consequences of amyloid and tau deposition. However, models of resilience have been constrained by reliance on measures of neuropathology, substantially limiting the number of participants available for analysis.

Evaluating the association of genotype and cognitive resilience in SuperAgers.

Introduction: "SuperAgers" are oldest-old adults (ages 80+) whose memory performance more closely resembles middle-aged adults. The present study examined allele frequency in non-Hispanic Black (NHB) and non-Hispanic White (NHW) SuperAgers compared to controls and Alzheimer's disease dementia cases.

Methods: In 18,080 participants from eight cohorts, harmonized clinical diagnostics and memory, executive function, and language domain scores were used to identify SuperAgers, cases, and controls across age-defined bins.

Deep learning-based free-water correction for single-shell diffusion MRI.

Free-water elimination (FWE) modeling in diffusion magnetic resonance imaging (dMRI) is crucial for accurate estimation of diffusion properties by mitigating the partial volume effects caused by free water, particularly at the interface between white matter and cerebrospinal fluid. The presence of free water partial volume effects leads to biases in estimating diffusion properties. Additionally, the existing mathematical FWE model is a two-compartment model, which can be well posed for multi-shell data.

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

Introduction: The effects of sex and apolipoprotein E (APOE)-Alzheimer's disease (AD) risk factors-on white matter microstructure are not well characterized.

Methods: Diffusion magnetic resonance imaging data from nine well-established longitudinal cohorts of aging were free water (FW)-corrected and harmonized. This dataset included 4741 participants (age = 73.

Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment.

Diffusion MRI derived free-water (FW) metrics show promise in predicting cognitive impairment and decline in aging and Alzheimer's disease (AD). FW is sensitive to subtle changes in brain microstructure, so it is possible these measures may be more sensitive than traditional structural neuroimaging biomarkers. In this study, we examined the associations among FW metrics (measured in the hippocampus and two AD signature meta-ROIs) with cognitive performance, and compared FW findings to those from more traditional neuroimaging biomarkers of AD.

Predicting Age from White Matter Diffusivity with Residual Learning.

Imaging findings inconsistent with those expected at specific chronological age ranges may serve as early indicators of neurological disorders and increased mortality risk. Estimation of chronological age, and deviations from expected results, from structural magnetic resonance imaging (MRI) data has become an important proxy task for developing biomarkers that are sensitive to such deviations. Complementary to structural analysis, diffusion tensor imaging (DTI) has proven effective in identifying age-related microstructural changes within the brain white matter, thereby presenting itself as a promising additional modality for brain age prediction.

Learning-based Free-Water Correction using Single-shell Diffusion MRI.

Diffusion magnetic resonance imaging (dMRI) offers the ability to assess subvoxel brain microstructure through the extraction of biomarkers like fractional anisotropy, as well as to unveil brain connectivity by reconstructing white matter fiber trajectories. However, accurate analysis becomes challenging at the interface between cerebrospinal fluid and white matter, where the MRI signal originates from both the cerebrospinal fluid and the white matter partial volume. The presence of free water partial volume effects introduces a substantial bias in estimating diffusion properties, thereby limiting the clinical utility of DWI.

Characterizing patterns of diffusion tensor imaging variance in aging brains.

Purpose: As large analyses merge data across sites, a deeper understanding of variance in statistical assessment across the sources of data becomes critical for valid analyses. Diffusion tensor imaging (DTI) exhibits spatially varying and correlated noise, so care must be taken with distributional assumptions. Here, we characterize the role of physiology, subject compliance, and the interaction of the subject with the scanner in the understanding of DTI variability, as modeled in the spatial variance of derived metrics in homogeneous regions.

Harmonized connectome resampling for variance in voxel sizes.

To date, there has been no comprehensive study characterizing the effect of diffusion-weighted magnetic resonance imaging voxel resolution on the resulting connectome for high resolution subject data. Similarity in results improved with higher resolution, even after initial down-sampling. To ensure robust tractography and connectomes, resample data to 1 mm isotropic resolution.

Sex, racial, and -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 () - 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.

Cortico-basal ganglia white matter microstructure is linked to restricted repetitive behavior in autism spectrum disorder.

Background: Restricted repetitive behavior (RRB) is one of two behavioral domains required for the diagnosis of autism spectrum disorder (ASD). Neuroimaging is widely used to study brain alterations associated with ASD and the domain of social and communication deficits, but there has been less work regarding brain alterations linked to RRB.

Methods: We utilized neuroimaging data from the National Institute of Mental Health Data Archive to assess basal ganglia and cerebellum structure in a cohort of children and adolescents with ASD compared to typically developing (TD) controls.

A deep neural network estimation of brain age is sensitive to cognitive impairment and decline.

The greatest known risk factor for Alzheimer's disease (AD) is age. While both normal aging and AD pathology involve structural changes in the brain, their trajectories of atrophy are not the same. Recent developments in artificial intelligence have encouraged studies to leverage neuroimaging-derived measures and deep learning approaches to predict brain age, which has shown promise as a sensitive biomarker in diagnosing and monitoring AD.

Predicting Age from White Matter Diffusivity with Residual Learning.

Imaging findings inconsistent with those expected at specific chronological age ranges may serve as early indicators of neurological disorders and increased mortality risk. Estimation of chronological age, and deviations from expected results, from structural magnetic resonance imaging (MRI) data has become an important proxy task for developing biomarkers that are sensitive to such deviations. Complementary to structural analysis, diffusion tensor imaging (DTI) has proven effective in identifying age-related microstructural changes within the brain white matter, thereby presenting itself as a promising additional modality for brain age prediction.

Longitudinal change in memory performance as a strong endophenotype for Alzheimer's disease.

Introduction: Although large-scale genome-wide association studies (GWAS) have been conducted on AD, few have been conducted on continuous measures of memory performance and memory decline.

Methods: We conducted a cross-ancestry GWAS on memory performance (in 27,633 participants) and memory decline (in 22,365 participants; 129,201 observations) by leveraging harmonized cognitive data from four aging cohorts.

Results: We found high heritability for two ancestry backgrounds.