Microstructural changes in the inferior tuberal hypothalamus correlate with daytime sleepiness in Lewy body disease.

Background: Excessive daytime sleepiness (EDS) is a disabling symptom of Lewy body disorders (LBD). The hypothalamus is a key sleep-wake regulator, but its contribution to EDS in LBD remains unclear. Objectives: Use diffusion MRI to evaluate the relationship of hypothalamic microstructure to EDS symptoms in LBD. Methods: We studied 102 patients with clinically-defined LBD (Parkinson's disease, n=93; Parkinson's disease dementia, n=4; and dementia with Lewy bodies, n=5) and Epworth Sleepiness Scale (ESS) within 2 years of MRI. Mean diffusivity (MD) was compared between EDS+ (ESS≥10, n=37) and EDS- (ESS<10, n=65) groups in the whole hypothalamus and three subregions, covarying for age and sex. Secondary analyses tested correlations between subregion MD and continuous ESS, global cognition, and motor scores; and between subregion volume and continuous ESS. Results: MD was increased in EDS+ compared to EDS-only in the inferior tuberal subregion (Cohen's d=0.43, p=0.043, ß=0.117±0.057), with trend level differences in the whole hypothalamus (Cohen's d=0.39, p=0.064, ß=0.070±0.037) and superior tuberal subregion (Cohen's d=0.38, p=0.073, ß=0.063±0.035). No difference was seen in the posterior subregion (Cohen's d=0.1, p=0.628, ß=0.019±0.038). Significant correlations with continuous ESS were seen in MD of whole hypothalamus (r 2 =0.074, p=0.0057), superior tuberal (r 2 =0.081, p=0.0038), and inferior tuberal (r 2 =0.073, p=0.0059) subregions. There was no correlation of hypothalamic MD with global cognition or motor scores, and no correlation of whole/subregional hypothalamic volumes with ESS. Conclusions: Daytime sleepiness associates with increased MD in the inferior tuberal hypothalamus in an LBD cohort. This suggests degeneration within this region could contribute to EDS symptoms.

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.

Cytoarchitectonic gradients of laminar degeneration in behavioural variant frontotemporal dementia.

Behavioral variant frontotemporal dementia (bvFTD) is a clinical syndrome primarily caused by either tau (bvFTD-tau) or TDP-43 (bvFTD-TDP) proteinopathies. We previously found lower cortical layers and dorsolateral regions accumulate greater tau than TDP-43 pathology; however, patterns of laminar neurodegeneration across diverse cytoarchitecture in bvFTD is understudied. We hypothesized that bvFTD-tau and bvFTD-TDP have distinct laminar distributions of pyramidal neurodegeneration along cortical gradients, a topologic order of cytoarchitectonic subregions based on increasing pyramidal density and laminar differentiation. Here, we tested this hypothesis in a frontal cortical gradient consisting of five cytoarchitectonic types (i.e., periallocortex, agranular mesocortex, dysgranular mesocortex, eulaminate-I isocortex, eulaminate-II isocortex) spanning anterior cingulate, paracingulate, orbitofrontal, and mid-frontal gyri in bvFTD-tau (n=27), bvFTD-TDP (n=47), and healthy controls (HC; n=32). We immunostained all tissue for total neurons (NeuN; neuronal-nuclear protein) and pyramidal neurons (SMI32; non-phosphorylated neurofilament) and digitally quantified NeuN-immunoreactivity (ir) and SMI32-ir in supragranular II-III, infragranular V-VI, and all I-VI layers in each cytoarchitectonic type. We used linear mixed-effects models adjusted for demographic and biologic variables to compare SMI32-ir between groups and examine relationships with the cortical gradient, long-range pathways, and clinical symptoms. We found regional and laminar distributions of SMI32-ir expected for HC, validating our measures within the cortical gradient framework. While SMI32-ir loss was relatively uniform along the cortical gradient in bvFTD-TDP, SMI32-ir progressively decreased along the cortical gradient of bvFTD-tau and included greater SMI32-ir loss in supragranular eulaminate-II isocortex in bvFTD-tau versus bvFTD-TDP (p=0.039). Using a ratio of SMI32-ir to model known long-range connectivity between infragranular mesocortex and supragranular isocortex, we found a larger laminar ratio in bvFTD-tau versus bvFTD-TDP (p=0.019), suggesting select long-projecting pathways may contribute to isocortical-predominant degeneration in bvFTD-tau. In cytoarchitectonic types with the highest NeuN-ir, we found lower SMI32-ir in bvFTD-tau versus bvFTD-TDP (p=0.047), suggesting pyramidal neurodegeneration may occur earlier in bvFTD-tau. Lastly, we found that reduced SMI32-ir related to behavioral severity and frontal-mediated letter fluency, not temporal-mediated confrontation naming, demonstrating the clinical relevance and specificity of frontal pyramidal neurodegeneration to bvFTD-related symptoms. Our data suggest loss of neurofilament-rich pyramidal neurons is a clinically relevant feature of bvFTD that selectively worsens along a frontal cortical gradient in bvFTD-tau, not bvFTD-TDP. Therefore, tau-mediated degeneration may preferentially involve pyramidal-rich layers that connect more distant cytoarchitectonic types. Moreover, the hierarchical arrangement of cytoarchitecture along cortical gradients may be an important neuroanatomical framework for identifying which types of cells and pathways are differentially involved between proteinopathies.

Epigenetic and genetic risk of Alzheimer disease from autopsied brains in two ethnic groups.

Genetic variants and epigenetic features both contribute to the risk of Alzheimer's disease (AD). We studied the AD association of CpG-related single nucleotide polymorphisms (CGS), which act as a hub of both the genetic and epigenetic effects, in Caribbean Hispanics (CH) and generalized the findings to Non-Hispanic Whites (NHW). First, we conducted a genome-wide, sliding-window-based association with AD, in 7,155 CH and 1,283 NHW participants. Next, using data from the dorsolateral prefrontal cortex in 179 CH brains, we tested the cis- and trans-effects of AD-associated CGS on brain DNA methylation to mRNA expression. For the genes with significant cis- and trans-effects, we investigated their enriched pathways. We identified six genetic loci in CH with CGS dosage associated with AD at genome-wide significance levels: ADAM20 (Score = 55.19, P = 4.06 × 10-8), the intergenic region between VRTN and SYNDIG1L (Score = - 37.67, P = 2.25 × 10-9), SPG7 (16q24.3) (Score = 40.51, P = 2.23 × 10-8), PVRL2 (Score = 125.86, P = 1.64 × 10-9), TOMM40 (Score = - 18.58, P = 4.61 × 10-8), and APOE (Score = 75.12, P = 7.26 × 10-26). CGSes in PVRL2 and APOE were also significant in NHW. Except for ADAM20, CGSes in the other five loci were associated with CH brain methylation levels (mQTLs) and CGSes in SPG7, PVRL2, and APOE were also mQTLs in NHW. Except for SYNDIG1L (P = 0.08), brain methylation levels in the other five loci affected downstream mRNA expression in CH (P < 0.05), and methylation at VRTN and TOMM40 were also associated with mRNA expression in NHW. Gene expression in these six loci were also regulated by CpG sites in genes that were enriched in the neuron projection and glutamatergic synapse pathways (FDR < 0.05). DNA methylation at all six loci and mRNA expression of SYNDIG1 and TOMM40 were significantly associated with Braak Stage in CH. In summary, we identified six CpG-related genetic loci associated with AD in CH, harboring both genetic and epigenetic risks. However, their downstream effects on mRNA expression maybe ethnic specific and different from NHW.

Baseline levels and longitudinal changes in plasma Aß42/40 among Black and white individuals.

Blood-based biomarkers of Alzheimer disease (AD) may facilitate testing of historically under-represented groups. The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to compare AD biomarkers in participants who identify their race as either Black or white. Plasma samples from 324 Black and 1,547 white participants underwent analysis with C2N Diagnostics' PrecivityAD test for Aß42 and Aß40. Compared to white individuals, Black individuals had higher average plasma Aß42/40 levels at baseline, consistent with a lower average level of amyloid pathology. Interestingly, this difference resulted from lower average levels of plasma Aß40 in Black participants. Despite the differences, Black and white individuals had similar longitudinal rates of change in Aß42/40, consistent with a similar rate of amyloid accumulation. Our results agree with multiple recent studies demonstrating a lower prevalence of amyloid pathology in Black individuals, and additionally suggest that amyloid accumulates consistently across both groups.

Beyond Macrostructure: Is There a Role for Radiomics Analysis in Neuroimaging ?

The most commonly used neuroimaging biomarkers of brain structure, particularly in neurodegenerative diseases, have traditionally been summary measurements from ROIs derived from structural MRI, such as volume and thickness. Advances in MR acquisition techniques, including high-field imaging, and emergence of learning-based methods have opened up opportunities to interrogate brain structure in finer detail, allowing investigators to move beyond macrostructural measurements. On the one hand, superior signal contrast has the potential to make appearance-based metrics that directly analyze intensity patterns, such as texture analysis and radiomics features, more reliable. Quantitative MRI, particularly at high-field, can also provide a richer set of measures with greater interpretability. On the other hand, use of neural networks-based techniques has the potential to exploit subtle patterns in images that can now be mined with advanced imaging. Finally, there are opportunities for integration of multimodal data at different spatial scales that is enabled by developments in many of the above techniques-for example, by combining digital histopathology with high-resolution ex-vivo and in-vivo MRI. Some of these approaches are at early stages of development and present their own set of challenges. Nonetheless, they hold promise to drive the next generation of validation and biomarker studies. This article will survey recent developments in this area, with a particular focus on Alzheimer's disease and related disorders. However, most of the discussion is equally relevant to imaging of other neurological disorders, and even to other organ systems of interest. It is not meant to be an exhaustive review of the available literature, but rather presented as a summary of recent trends through the discussion of a collection of representative studies with an eye towards what the future may hold.

Postmortem imaging reveals patterns of medial temporal lobe vulnerability to tau pathology in Alzheimer's disease.

Our current understanding of the spread and neurodegenerative effects of tau neurofibrillary tangles (NFTs) within the medial temporal lobe (MTL) during the early stages of Alzheimer's Disease (AD) is limited by the presence of confounding non-AD pathologies and the two-dimensional (2-D) nature of conventional histology studies. Here, we combine ex vivo MRI and serial histological imaging from 25 human MTL specimens to present a detailed, 3-D characterization of quantitative NFT burden measures in the space of a high-resolution, ex vivo atlas with cytoarchitecturally-defined subregion labels, that can be used to inform future in vivo neuroimaging studies. Average maps show a clear anterior to poster gradient in NFT distribution and a precise, spatial pattern with highest levels of NFTs found not just within the transentorhinal region but also the cornu ammonis (CA1) subfield. Additionally, we identify granular MTL regions where measures of neurodegeneration are likely to be linked to NFTs specifically, and thus potentially more sensitive as early AD biomarkers.

Automatic segmentation of medial temporal lobe subregions in multi-scanner, multi-modality MRI of variable quality.

Background: Volumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer's disease. However, image quality may vary in MRI. Poor quality MR images can lead to unreliable segmentation of MTL subregions. Considering that different MRI contrast mechanisms and field strengths (jointly referred to as "modalities" here) offer distinct advantages in imaging different parts of the MTL, we developed a muti-modality segmentation model using both 7 tesla (7T) and 3 tesla (3T) structural MRI to obtain robust segmentation in poor-quality images. Method: MRI modalities including 3T T1-weighted, 3T T2-weighted, 7T T1-weighted and 7T T2-weighted (7T-T2w) of 197 participants were collected from a longitudinal aging study at the Penn Alzheimer's Disease Research Center. Among them, 7T-T2w was used as the primary modality, and all other modalities were rigidly registered to the 7T-T2w. A model derived from nnU-Net took these registered modalities as input and outputted subregion segmentation in 7T-T2w space. 7T-T2w images most of which had high quality from 25 selected training participants were manually segmented to train the multi-modality model. Modality augmentation, which randomly replaced certain modalities with Gaussian noise, was applied during training to guide the model to extract information from all modalities. To compare our proposed model with a baseline single-modality model in the full dataset with mixed high/poor image quality, we evaluated the ability of derived volume/thickness measures to discriminate Amyloid+ mild cognitive impairment (A+MCI) and Amyloid- cognitively unimpaired (A-CU) groups, as well as the stability of these measurements in longitudinal data. Results: The multi-modality model delivered good performance regardless of 7T-T2w quality, while the single-modality model under-segmented subregions in poor-quality images. The multi-modality model generally demonstrated stronger discrimination of A+MCI versus A-CU. Intra-class correlation and Bland-Altman plots demonstrate that the multi-modality model had higher longitudinal segmentation consistency in all subregions while the single-modality model had low consistency in poor-quality images. Conclusion: The multi-modality MRI segmentation model provides an improved biomarker for neurodegeneration in the MTL that is robust to image quality. It also provides a framework for other studies which may benefit from multimodal imaging.

α-Synuclein Conformations in Plasma Distinguish Parkinson's Disease from Dementia with Lewy Bodies.

Spread and aggregation of misfolded α-synuclein (aSyn) within the brain is the pathologic hallmark of Lewy body diseases (LBD), including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). While evidence exists for multiple aSyn protein conformations, often termed "strains" for their distinct biological properties, it is unclear whether PD and DLB result from aSyn strain differences, and biomarkers that differentiate PD and DLB are lacking. Moreover, while pathological forms of aSyn have been detected outside the brain ( e.g., in skin, gut, blood), the functional significance of these peripheral aSyn species is unclear. Here, we developed assays using monoclonal antibodies selective for two different aSyn species generated in vitro - termed Strain A and Strain B - and used them to evaluate human brain tissue, cerebrospinal fluid (CSF), and plasma, through immunohistochemistry, enzyme-linked immunoassay, and immunoblotting. Surprisingly, we found that plasma aSyn species detected by these antibodies differentiated individuals with PD vs. DLB in a discovery cohort (UPenn, n=235, AUC 0.83) and a multi-site replication cohort (Parkinson's Disease Biomarker Program, or PDBP, n=200, AUC 0.72). aSyn plasma species detected by the Strain A antibody also predicted rate of cognitive decline in PD. We found no evidence for aSyn strains in CSF, and ability to template aSyn fibrillization differed for species isolated from plasma vs. brain, and in PD vs. DLB. Taken together, our findings suggest that aSyn conformational differences may impact clinical presentation and cortical spread of pathological aSyn. Moreover, the enrichment of these aSyn strains in plasma implicates a non-central nervous system source.

Medial temporal lobe gray matter microstructure in preclinical Alzheimer's disease.

INTRODUCTION: Typical MRI measures of neurodegeneration have limited sensitivity in early disease stages. Diffusion MRI (dMRI) microstructural measures may allow for detection in preclinical stages. METHODS: Participants had dMRI and either beta-amyloid PET or plasma biomarkers of Alzheimer's pathology within 18 months of MRI. Microstructure was measured in portions of the medial temporal lobe (MTL) with high neurofibrillary tangle (NFT) burden based on a previously developed post mortem 3D-map. Regressions examined relationships between microstructure and markers of Alzheimer's pathology in preclinical disease and then across disease stages. RESULTS: There was higher isometric volume fraction in amyloid-positive compared to amyloid-negative cognitively unimpaired individuals in high tangle MTL regions. Similarly, plasma biomarkers and 18F-flortaucipir were associated with microstructural changes in preclinical disease. Additional microstructural effects were seen across disease stages. DISCUSSION: Combining a post mortem atlas of NFT pathology with microstructural measures allows for detection of neurodegeneration in preclinical Alzheimer's disease. Highlights Typical markers of neurodegeneration are not sensitive in preclinical Alzheimer's. dMRI measured microstructure in regions with high NFT. Microstructural changes occur in medial temporal regions in preclinical disease. Microstructural changes occur in other typical Alzheimer's regions in later stages. Combining post mortem pathology atlases with in vivo MRI is a powerful framework.

Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease.

Identifying individuals with early stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would allow professionals and loved ones to make better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. In this study, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes (Posterior Cortical Atrophy, logopenic variant Primary Progressive Aphasia, and amnestic syndrome with multi-domain impairment and age of onset < 65 years). All patients underwent structural magnetic resonance imaging (MRI), tau (18F-Flortaucipir) PET, and amyloid (either 18F-Florbetaben or 11C-Pittsburgh Compound B) PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Our sample of early atypical AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, d = 0.95. These AD patients showed prominent baseline tau burden in posterior cortical regions including the major nodes of the default mode network, including the angular gyrus, posterior cingulate cortex/precuneus, and lateral temporal cortex. Greater baseline tau in the broader default mode network predicted faster clinical decline. Tau in the default mode network was the strongest predictor of clinical decline, outperforming baseline clinical impairment, tau in other functional networks, and the magnitude of cortical atrophy and amyloid burden in the default mode network. Overall, these findings point to the contribution of baseline tau burden within the default mode network of the cerebral cortex to predicting the magnitude of clinical decline in a sample of atypical early AD patients one year later. This simple measure based on a tau PET scan could aid the development of a personalized prognostic, monitoring, and treatment plan tailored to each individual patient, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.

Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease.

Introduction: Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes. Materials and methods: Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics. Results: Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs. Discussion: We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.

Cytoarchitectonic gradients of laminar degeneration in behavioral variant frontotemporal dementia.

Behavioral variant frontotemporal dementia (bvFTD) is a clinical syndrome primarily caused by either tau (bvFTD-tau) or TDP-43 (bvFTD-TDP) proteinopathies. We previously found lower cortical layers and dorsolateral regions accumulate greater tau than TDP-43 pathology; however, patterns of laminar neurodegeneration across diverse cytoarchitecture in bvFTD is understudied. We hypothesized that bvFTD-tau and bvFTD-TDP have distinct laminar distributions of pyramidal neurodegeneration along cortical gradients, a topologic order of cytoarchitectonic subregions based on increasing pyramidal density and laminar differentiation. Here, we tested this hypothesis in a frontal cortical gradient consisting of five cytoarchitectonic types (i.e., periallocortex, agranular mesocortex, dysgranular mesocortex, eulaminate-I isocortex, eulaminate-II isocortex) spanning anterior cingulate, paracingulate, orbitofrontal, and mid-frontal gyri in bvFTD-tau (n=27), bvFTD-TDP (n=47), and healthy controls (HC; n=32). We immunostained all tissue for total neurons (NeuN; neuronal-nuclear protein) and pyramidal neurons (SMI32; non-phosphorylated neurofilament) and digitally quantified NeuN-immunoreactivity (ir) and SMI32-ir in supragranular II-III, infragranular V-VI, and all I-VI layers in each cytoarchitectonic type. We used linear mixed-effects models adjusted for demographic and biologic variables to compare SMI32-ir between groups and examine relationships with the cortical gradient, long-range pathways, and clinical symptoms. We found regional and laminar distributions of SMI32-ir expected for HC, validating our measures within the cortical gradient framework. While SMI32-ir loss was not related to the cortical gradient in bvFTD-TDP, SMI32-ir progressively decreased along the cortical gradient of bvFTD-tau and included greater SMI32-ir loss in supragranular eulaminate-II isocortex in bvFTD-tau vs bvFTD-TDP ( p =0.039). In a structural model for long-range laminar connectivity between infragranular mesocortex and supragranular isocortex, we found a larger laminar ratio of mesocortex-to-isocortex SMI32-ir in bvFTD-tau vs bvFTD-TDP ( p =0.019), suggesting select long-projecting pathways may contribute to isocortical-predominant degeneration in bvFTD-tau. In cytoarchitectonic types with the highest NeuN-ir, we found lower SMI32-ir in bvFTD-tau vs bvFTD-TDP ( p =0.047), suggesting pyramidal neurodegeneration may occur earlier in bvFTD-tau. Lastly, we found that reduced SMI32-ir related to behavioral severity and frontal-mediated letter fluency, not temporal-mediated confrontation naming, demonstrating the clinical relevance and specificity of frontal pyramidal neurodegeneration to bvFTD-related symptoms. Our data suggest loss of neurofilament-rich pyramidal neurons is a clinically relevant feature of bvFTD that selectively worsens along a frontal cortical gradient in bvFTD-tau, not bvFTD-TDP. Therefore, tau-mediated degeneration may preferentially involve pyramidal-rich layers that connect more distant cytoarchitectonic types. Moreover, the hierarchical arrangement of cytoarchitecture along cortical gradients may be an important neuroanatomical framework for identifying which types of cells and pathways are differentially involved between proteinopathies.

Pathologic and cognitive correlates of plasma biomarkers in neurodegenerative disease.

INTRODUCTION: We investigate pathological correlates of plasma phosphorylated tau 181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) across a clinically diverse spectrum of neurodegenerative disease, including normal cognition (NormCog) and impaired cognition (ImpCog). METHODS: Participants were NormCog (n = 132) and ImpCog (n = 461), with confirmed ß-amyloid (Aß+/-) status (cerebrospinal fluid, positron emission tomography, autopsy) and single molecule array plasma measurements. Logistic regression and receiver operating characteristic (ROC) area under the curve (AUC) tested how combining plasma analytes discriminated Aß+ from Aß-. Survival analyses tested time to clinical dementia rating (global CDR) progression. RESULTS: Multivariable models (p-tau+GFAP+NfL) had the best performance to detect Aß+ in NormCog (ROCAUC = 0.87) and ImpCog (ROCAUC = 0.87). Survival analyses demonstrated that higher NfL best predicted faster CDR progression for both Aß+ (hazard ratio [HR] = 2.94; p = 8.1e-06) and Aß- individuals (HR = 3.11; p = 2.6e-09). DISCUSSION: Combining plasma biomarkers can optimize detection of Alzheimer's disease (AD) pathology across cognitively normal and clinically diverse neurodegenerative disease. HIGHLIGHTS: Participants were clinically heterogeneous, with autopsy- or biomarker-confirmed Aß. Combining plasma p-tau181, GFAP, and NfL improved diagnostic accuracy for Aß status. Diagnosis by plasma biomarkers is more accurate in amnestic AD than nonamnestic AD. Plasma analytes show independent associations with tau PET and post mortem Aß/tau. Plasma NfL predicted longitudinal cognitive decline in both Aß+ and Aß- individuals.

Automated Quality Evaluation Index for Arterial Spin Labeling Derived Cerebral Blood Flow Maps.

BACKGROUND: Arterial spin labeling (ASL) derived cerebral blood flow (CBF) maps are prone to artifacts and noise that can degrade image quality. PURPOSE: To develop an automated and objective quality evaluation index (QEI) for ASL CBF maps. STUDY TYPE: Retrospective. POPULATION: Data from N = 221 adults, including patients with Alzheimer's disease (AD), Parkinson's disease, and traumatic brain injury. FIELD STRENGTH/SEQUENCE: Pulsed or pseudocontinuous ASL acquired at 3 T using non-background suppressed 2D gradient-echo echoplanar imaging or background suppressed 3D spiral spin-echo readouts. ASSESSMENT: The QEI was developed using N = 101 2D CBF maps rated as unacceptable, poor, average, or excellent by two neuroradiologists and validated by 1) leave-one-out cross validation, 2) assessing if CBF reproducibility in N = 53 cognitively normal adults correlates inversely with QEI, 3) if iterative discarding of low QEI data improves the Cohen's d effect size for CBF differences between preclinical AD (N = 27) and controls (N = 53), 4) comparing the QEI with manual ratings for N = 50 3D CBF maps, and 5) comparing the QEI with another automated quality metric. STATISTICAL TESTS: Inter-rater reliability and manual vs. automated QEI were quantified using Pearson's correlation. P < 0.05 was considered significant. RESULTS: The correlation between QEI and manual ratings (R = 0.83, CI: 0.76-0.88) was similar (P = 0.56) to inter-rater correlation (R = 0.81, CI: 0.73-0.87) for the 2D data. CBF reproducibility correlated negatively (R = -0.74, CI: -0.84 to -0.59) with QEI. The effect size comparing patients and controls improved (R = 0.72, CI: 0.59-0.82) as low QEI data was discarded iteratively. The correlation between QEI and manual ratings (R = 0.86, CI: 0.77-0.92) of 3D ASL was similar (P = 0.09) to inter-rater correlation (R = 0.78, CI: 0.64-0.87). The QEI correlated (R = 0.87, CI: 0.77-0.92) significantly better with manual ratings than did an existing approach (R = 0.54, CI: 0.30-0.72). DATA CONCLUSION: Automated QEI performed similarly to manual ratings and can provide scalable ASL quality control. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Multi-omics Characterization of Epigenetic and Genetic Risk of Alzheimer Disease in Autopsied Brains from two Ethnic Groups.

Background: Both genetic variants and epigenetic features contribute to the risk of Alzheimer's disease (AD). We studied the AD association of CpG-related single nucleotide polymorphisms (CGS), which act as the hub of both the genetic and epigenetic effects, in Hispanics decedents and generalized the findings to Non-Hispanic Whites (NHW) decedents. Methods: First, we derived the dosage of the CpG site-creating allele of multiple CGSes in each 1 KB window across the genome and we conducted a sliding window association test with clinical diagnosis of AD in 7,155 Hispanics (3,194 cases and 3,961 controls) using generalized linear mixed models with the adjustment of age, sex, population structure, genomic relationship matrix, and genotyping batches. Next, using methylation and bulk RNA-sequencing data from the dorsolateral pre-frontal cortex in 150 Hispanics brains, we tested the cis- and trans-effects of AD associated CGS on brain DNA methylation to mRNA expression. For the genes with significant cis- and trans-effects, we checked their enriched pathways. Results: We identified six genetic loci in Hispanics with CGS dosage associated with AD at genome-wide significance levels: ADAM20 (Score=55.2, P= 4.06×10 -8 ), between VRTN (Score=-19.6, P= 1.47×10 -8 ) and SYNDIG1L (Score=-37.7, P= 2.25×10 -9 ), SPG7 (16q24.3) (Score=40.5, P= 2.23×10 -8 ), PVRL2 (Score=125.86, P= 1.64×10 -9 ), TOMM40 (Score=-18.58, P= 4.61×10 -8 ), and APOE (Score=75.12, P= 7.26×10 -26 ). CGSes in PVRL2 and APOE were also genome-wide significant in NHW. Except for ADAM20 , CGSes in all the other five loci were associated with Hispanic brain methylation levels (mQTLs) and CGSes in SPG7, PVRL2, and APOE were also mQTLs in NHW. Except for SYNDIG1L ( P =0.08), brain methylation levels in all the other five loci affected downstream RNA expression in the Hispanics ( P <0.05), and methylation at VRTN and TOMM40 were also associated with RNA expression in NHW. Gene expression in these six loci were also regulated by CpG sites in genes that were enriched in the neuron projection and synapse (FDR<0.05). Conclusions: We identified six CpG associated genetic loci associated with AD in Hispanics, harboring both genetic and epigenetic risks. However, their downstream effects on mRNA expression maybe ethnic specific and different from NHW.

Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals.

Importance: Brain aging elicits complex neuroanatomical changes influenced by multiple age-related pathologies. Understanding the heterogeneity of structural brain changes in aging may provide insights into preclinical stages of neurodegenerative diseases. Objective: To derive subgroups with common patterns of variation in participants without diagnosed cognitive impairment (WODCI) in a data-driven manner and relate them to genetics, biomedical measures, and cognitive decline trajectories. Design, Setting, and Participants: Data acquisition for this cohort study was performed from 1999 to 2020. Data consolidation and harmonization were conducted from July 2017 to July 2021. Age-specific subgroups of structural brain measures were modeled in 4 decade-long intervals spanning ages 45 to 85 years using a deep learning, semisupervised clustering method leveraging generative adversarial networks. Data were analyzed from July 2021 to February 2023 and were drawn from the Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) international consortium. Individuals WODCI at baseline spanning ages 45 to 85 years were included, with greater than 50 000 data time points. Exposures: Individuals WODCI at baseline scan. Main Outcomes and Measures: Three subgroups, consistent across decades, were identified within the WODCI population. Associations with genetics, cardiovascular risk factors (CVRFs), amyloid ß (Aß), and future cognitive decline were assessed. Results: In a sample of 27 402 individuals (mean [SD] age, 63.0 [8.3] years; 15 146 female [55%]) WODCI, 3 subgroups were identified in contrast with the reference group: a typical aging subgroup, A1, with a specific pattern of modest atrophy and white matter hyperintensity (WMH) load, and 2 accelerated aging subgroups, A2 and A3, with characteristics that were more distinct at age 65 years and older. A2 was associated with hypertension, WMH, and vascular disease-related genetic variants and was enriched for Aß positivity (ages ≥65 years) and apolipoprotein E (APOE) ε4 carriers. A3 showed severe, widespread atrophy, moderate presence of CVRFs, and greater cognitive decline. Genetic variants associated with A1 were protective for WMH (rs7209235: mean [SD] B = -0.07 [0.01]; P value = 2.31 × 10-9) and Alzheimer disease (rs72932727: mean [SD] B = 0.1 [0.02]; P value = 6.49 × 10-9), whereas the converse was observed for A2 (rs7209235: mean [SD] B = 0.1 [0.01]; P value = 1.73 × 10-15 and rs72932727: mean [SD] B = -0.09 [0.02]; P value = 4.05 × 10-7, respectively); variants in A3 were associated with regional atrophy (rs167684: mean [SD] B = 0.08 [0.01]; P value = 7.22 × 10-12) and white matter integrity measures (rs1636250: mean [SD] B = 0.06 [0.01]; P value = 4.90 × 10-7). Conclusions and Relevance: The 3 subgroups showed distinct associations with CVRFs, genetics, and subsequent cognitive decline. These subgroups likely reflect multiple underlying neuropathologic processes and affect susceptibility to Alzheimer disease, paving pathways toward patient stratification at early asymptomatic stages and promoting precision medicine in clinical trials and health care.

Neighborhood disadvantage reduces cognitive reserve independent of neuropathologic change.

INTRODUCTION: Individuals in socioeconomically disadvantaged neighborhoods exhibit increased risk for impaired cognitive function. Whether this association relates to the major dementia-related neuropathologies is unknown. METHODS: This cross-sectional study included 469 autopsy cases from 2011 to 2023. The relationships between neighborhood disadvantage measured by Area Deprivation Index (ADI) percentiles categorized into tertiles, cognition evaluated by the last Mini-Mental State Examination (MMSE) scores before death, and 10 dementia-associated proteinopathies and cerebrovascular disease were assessed using regression analyses. RESULTS: Higher ADI was significantly associated with lower MMSE score. This was mitigated by increasing years of education. ADI was not associated with an increase in dementia-associated neuropathologic change. Moreover, the significant association between ADI and cognition remained even after controlling for changes in major dementia-associated proteinopathies or cerebrovascular disease. DISCUSSION: Neighborhood disadvantage appears to be associated with decreased cognitive reserve. This association is modified by education but is independent of the major dementia-associated neuropathologies.

Gene-SGAN: discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering.

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and single nucleotide polymorphism data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-associated neuroimaging phenotypes.