Biology subjects

DeCarli, C.

Publications and source records attributed to DeCarli, C..

13 recordsLinked to original sources

bioRxiv2025

Multimodal MRI Insights into Glymphatic Clearance and Blood-Brain Barrier Integrity in Healthy Aging

Aging is associated with impaired CSF clearance in preclinical models, but its impact on blood-brain barrier (BBB) health and glymphatic function in humans remains unclear. We aimed to compare healthy younger and older adults using multimodal MRI to assess age-related changes in BBB permeability and glymphatic clearance, and to examine the relationships between these measures. Thirty participants were recruited (12 younger, 26 {+/-} 3 years; 18 older, 75 {+/-} 7 years). Diffusion-prepared arterial spin labeling measured the water exchange rate (Kw) across the BBB; free water (FW) imaging quantified extracellular free water in white matter; and diffusion tensor imaging along perivascular spaces (DTI-ALPS) assessed glymphatic function. Older individuals showed reduced whole-brain Kw (p=0.021), increased white matter FW (p=0.002), and reduced DTI-ALPS (p<0.001) compared to younger adults. Kw associated with both DTI-ALPS ({beta}=0.402x10-2, p=0.022) and FW ({beta}=-0.676x10-3, p=0.008). Reduced Kw may reflect impaired BBB function, while reduced DTI-ALPS and increased FW indicate impaired glymphatic clearance. FW partially mediated the relationship between Kw and DTI-ALPS, suggesting a potential mechanistic link. Overall, this study provides novel multimodal MRI insights into BBB and glymphatic alterations in healthy aging and may inform the development of MRI biomarkers to preserve cognitive health.

neuroscience↗

bioRxiv2024

Kinetic modeling of 18F-PI-2620 binding in the brain using an image-derived input function with total-body PET

Accurate quantification of tau binding from 18F-PI-2620 PET requires kinetic modeling and an input function. Here, we implemented a non-invasive Image-derived input function (IDIF) derived using the state-of-the-art total-body uEXPLORER PET/CT scanner to quantify tau binding and tracer delivery rate from 18F-PI-2620 in the brain. Additionally, we explored the impact of scan duration on the quantification of kinetic parameters. Total-body PET dynamic data from 15 elderly participants were acquired. Time-activity curves from the grey matter regions of interest (ROIs) were fitted to the two-tissue compartmental model (2TCM) using a subject-specific IDIF derived from the descending aorta. ROI-specific kinetic parameters were estimated for different scan durations ranging from 10 to 90 minutes. Logan graphical analysis was also used to estimate the total distribution volume (VT). Differences in kinetic parameters were observed between ROIs, including significant reduction in tracer delivery rate (K1) in the medial temporal lobe. All kinetic parameters remained relatively stable after the 60-minute scan window across all ROIs, with K1 showing high stability after 30 minutes of scan duration. Excellent correlation was observed between VT estimated using 2TCM and Logan plot analysis. This study demonstrated the utility of IDIF with total-body PET in investigating 18F-PI-2620 kinetics in the brain.

neuroscience↗

bioRxiv2024

Learning precise segmentation of neurofibrillary tangles from rapid manual point annotations

Accumulation of abnormal tau protein into neurofibrillary tangles (NFTs) is a pathologic hallmark of Alzheimer disease (AD). Accurate detection of NFTs in tissue samples can reveal relationships with clinical, demographic, and genetic features through deep phenotyping. However, expert manual analysis is time-consuming, subject to observer variability, and cannot handle the data amounts generated by modern imaging. We present a scalable, open-source, deep-learning approach to quantify NFT burden in digital whole slide images (WSIs) of post-mortem human brain tissue. To achieve this, we developed a method to generate detailed NFT boundaries directly from single-point-per-NFT annotations. We then trained a semantic segmentation model on 45 annotated 2400{micro}m by 1200{micro}m regions of interest (ROIs) selected from 15 unique temporal cortex WSIs of AD cases from three institutions (University of California (UC)-Davis, UC-San Diego, and Columbia University). Segmenting NFTs at the single-pixel level, the model achieved an area under the receiver operating characteristic of 0.832 and an F1 of 0.527 (196-fold over random) on a held-out test set of 664 NFTs from 20 ROIs (7 WSIs). We compared this to deep object detection, which achieved comparable but coarser-grained performance that was 60% faster. The segmentation and object detection models correlated well with expert semi-quantitative scores at the whole-slide level (Spearmans rho {rho}=0.654 (p=6.50e-5) and {rho}=0.513 (p=3.18e-3), respectively). We openly release this multi-institution deep-learning pipeline to provide detailed NFT spatial distribution and morphology analysis capability at a scale otherwise infeasible by manual assessment.

pathology↗

bioRxiv2023

Sexually dimorphic differences in angiogenesis markers predict brain aging trajectories

Aberrant angiogenesis could contribute to cognitive impairment, representing a therapeutic target for preventing dementia. However, most angiogenesis studies focus on model organisms. To test the relevance of angiogenesis to human cognitive aging, we evaluated associations of circulating blood markers of angiogenesis with brain aging trajectories in two deeply phenotyped human cohorts (n=435, age 74+9) with longitudinal cognitive assessments, biospecimens, structural brain imaging, and clinical data. Machine learning and traditional statistics revealed sex dimorphic associations of plasma angiogenic growth factors with brain aging outcomes. Specifically, angiogenesis is associated with higher executive function and less brain atrophy in younger women (not men), a directionality of association that reverses around age 75. Higher levels of basic fibroblast growth factor, known for pleiotropic effects on multiple cell types, predicted favorable cognitive trajectories. This work demonstrates the relevance of angiogenesis to brain aging with important therapeutic implications for vascular cognitive impairment and dementia.

neuroscience↗

bioRxiv2023

Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels

Precise, scalable, and quantitative evaluation of whole slide images is crucial in neuropathology. We release a deep learning model for rapid object detection and precise information on the identification, locality, and counts of cored plaques and cerebral amyloid angiopathies (CAAs). We trained this object detector using a repurposed image-tile dataset without any human-drawn bounding boxes. We evaluated the detector on a new manually-annotated dataset of whole slide images (WSIs) from three institutions, four staining procedures, and four human experts. The detector matched the cohort of neuropathology experts, achieving 0.64 (model) vs. 0.64 (cohort) average precision (AP) for cored plaques and 0.75 vs. 0.51 AP for CAAs at a 0.5 IOU threshold. It provided count and locality predictions that correlated with gold-standard CERAD-like WSI scoring (p=0.07{+/-} 0.10). The openly-available model can quickly score WSIs in minutes without a GPU on a standard workstation.

pathology↗

bioRxiv2022

Cerebral Small Vessel Disease Burden is Associated with Decreased Abundance of Gut Barnesiella intestinihominis Bacterium in the Framingham Heart Study

A bidirectional communication exists between the brain and the gut, in which the gut microbiota influences cognitive function and vice-versa. Gut dysbiosis has been linked to several diseases, including Alzheimers disease and related dementias (ADRD). However, the relationship between gut dysbiosis and markers of cerebral small vessel disease (cSVD), a major contributor to ADRD, is unknown. In this cross-sectional study, we examined the connection between the gut microbiome, cognitive, and neuroimaging markers of cSVD in the Framingham Heart Study (FHS). Markers of cSVD included white matter hyperintensities (WMH), peak width of skeletonized mean diffusivity (PSMD), and executive function (EF), estimated as the difference between the trail-making tests B and A. We included 972 FHS participants with MRI scans, neurocognitive measures, and stool samples and quantified the gut microbiota composition using 16S rRNA sequencing. We used multivariable association and differential abundance analyses adjusting for age, sex, BMI, and education level to estimate the association between gut microbiota and WMH, PSMD, and EF measures. Our results suggest an increased abundance of Pseudobutyrivibrio and Ruminococcus genera was associated with lower WMH and PSMD (p-values < 0.001), as well as better executive function (p-values < 0.01). In addition, in both differential and multivariable analyses, we found that the gram-negative bacterium Barnesiella intestinihominis was strongly associated with markers indicating a higher cSVD burden. Finally, functional analyses using PICRUSt implicated various KEGG pathways, including microbial quorum sensing, AMP/GMP-activated protein kinase, phenylpyruvate, and {beta}-hydroxybutyrate production previously associated with cognitive performance and dementia. Our study provides important insights into the association between the gut microbiome and cSVD, but further studies are needed to replicate the findings.

neuroscience↗

bioRxiv2022

Brain signatures for neuropsychological and everyday memory achieve high replicability and explanatory power in two data cohorts

BackgroundThe "brain signature of cognition" concept has garnered interest as a data-driven, exploratory approach to better understand key brain regions involved in specific cognitive functions, with the potential to maximally characterize brain substrates of clinical outcomes. However, to be a robust brain phenotype, the signature approach requires a statistical foundation showing that model performance replicates across a variety of cohorts. Here, we outline a procedure that provides this foundation for a signature models of two memory-related behavioral domains. MethodIn each of two independent data cohorts, we derived regional brain gray matter thickness associations for neuropsychological and everyday cognition memory, testing for replicability. In each cohort we computed regional association to outcome in 40 randomly selected "discovery subsets" of size N = 400; we generated spatial overlap frequency maps and selected high-frequency regions as "consensus" signature masks for each cohort. We tested replicability by comparing cohort-based consensus model fits in all discovery sets. We tested explanatory power in each full cohort, compare signature model fits with competing "standard" models of each outcome. ResultSpatial replications produced strongly convergent consensus signature regions derived from UCD and ADNI. Consensus model fits were highly correlated in 40 random subsets of each cohort indicating high replicability. In comparisons over each full cohort, signature models outperformed other models with one exception. ConclusionMultiple random model generations, followed by consensus selection of regional brain substrates, produced signature models that replicated model fits to outcome and outperformed other commonly used measures. Robust biomarkers of cognition and everyday function may be achievable by this method. FundingThis project was funded by R01 AG052132 (NIH/NIA)

neuroscience↗

bioRxiv2020

Genetic variants for head size share genes and pathways with cancer

The size of the human head is determined by growth in the first years of life, while the rest of the body typically grows until early adulthood1. Such complex developmental processes are regulated by various genes and growth pathways2. Rare genetic syndromes have revealed genes that affect head size3, but the genetic drivers of variation in head size within the general population remain largely unknown. To elucidate biological pathways underlying the growth of the human head, we performed the largest genome-wide association study on human head size to date (N = 79,107). We identified 67 genetic loci, 50 of which are novel, and found that these loci are preferentially associated with head size and mostly independent from height. In subsequent neuroimaging analyses, the majority of genetic variants demonstrated widespread effects on the brain, whereas the effects of 17 variants could be localized to one or two specific brain regions. Through hypothesis-free approaches, we find a strong overlap of head size variants with both cancer pathways and cancer genes. Gene set analyses showed enrichment for different types of cancer and the p53, Wnt and ErbB signalling pathway. Genes overlapping or close to lead variants - such as TP53, PTEN and APC - were enriched for genes involved in macrocephaly syndromes (up to 37-fold) and high-fidelity cancer genes (up to 9-fold), whereas this enrichment was not seen for human height variants. This indicates that genes regulating early brain and cranial growth are associated with a propensity to neoplasia later in life, irrespective of height. Our results warrant further investigations of the link between head size and cancer, as well as its clinical implications in the general population.

genomics↗

bioRxiv2019

Endothelial-derived exosomes demonstrate a link between endothelial innate inflammation and brain dysfunction and injury in aging

We test the hypothesis that endothelial cells take on an inflammatory phenotype in functionally intact human subjects with radiographic evidence of white matter injury. Markers within all three complement effector pathways and regulatory proteins were quantified from endothelial-derived exosomes (EDE) of subjects (age 70-82) with (n=11) and without (n=16) evidence of white matter hyperintensity on MRI. Group differences and associations with systemic markers of immune activation (IL6, ICAM1), cognition and neuroimaging were calculated via regression modelling.\n\nEDE complement factors within the alternative and classical pathways were found to be higher and regulatory proteins lower in subjects with WMH. EDE levels of several factors demonstrated significant associations with cognitive slowing and systolic blood pressure. The inhibitor of the membrane attack complex, CD46, showed a significant positive association with cerebral grey matter volume. Systemic inflammatory markers, IL6 and ICAM1, were positively associated with EDE levels of several factors.\n\nThese findings provide the first in vivo evidence of the association of endothelial cell inflammation with white matter injury, cognition, and brain degeneration in functionally normal older individuals, and form the basis for future biomarker development in early or preclinical stages of vascular cognitive impairment and dementia.

neuroscience↗

bioRxiv2019

Endothelial CXCL5 negatively regulates myelination and repair after white matter stroke

Cerebral small vessel disease and resulting white matter pathologies are worsened by cardiovascular risk factors including obesity. The molecular changes in cerebral endothelial cells caused by chronic cerebrovascular risk factors remain unknown. We developed a novel approach for molecular profiling of chronically injured cerebral endothelial cells using cell-specific translating ribosome affinity purification (RiboTag) with RNA-seq in Tie2-Cre:RiboTag mice. We used this approach to identify the transcriptome of white matter endothelial cells after the onset of diet-induced obesity (DIO). DIO induces an IL-17B signaling pathway that acts on the cerebral endothelia through IL-17Rb to increase levels of both circulating CXCL5 and local endothelial expression of CXCL5 in both the DIO mouse model and in humans with imaging or pathologic evidence of cerebral small vessel disease. In the white matter, endothelial CXCL5 acts as a chemoattractant and promotes the association of oligodendrocyte progenitor cells (OPCs) with cerebral endothelia increasing vessel-associated OPC cell number and triggers OPC gene expression programs regulating migration and chemokine receptor activation. Targeted blockade of IL-17B with peripheral antibody administration reduced the population of vessel-associated OPCs by reducing endothelial CXCL5 expression. CXCL5-mediated sequestration of OPCs to white matter vasculature impairs OPC differentiation after a focal white matter ischemic lesion. DIO promotes a unique white matter endothelial-to-oligodendrocyte progenitor cell signaling pathway that compromises brain repair after stroke.

neuroscience↗

bioRxiv2018

Interpretable classification of Alzheimer’s disease pathologies with a convolutional neural network pipeline

Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and can lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline identifying specific neuropathologies--amyloid plaques and cerebral amyloid angiopathy--in immunohistochemical-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotated >70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieved strong plaque classification (0.993 and 0.744 areas under the receiver operating characteristic and precision recall curve, respectively) on a 10 WSI hold-out set. Prediction confidence maps visualized morphology distributions from the full-WSI level down to 20x magnification. Resulting plaque-burden scores correlated well with established semi-quantitative scores. Finally, saliency mapping demonstrated that networks learned patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologists ability may suggest a route to neuropathologic deep phenotyping.

pathology↗

bioRxiv2018

Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,822 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 161 genome-wide significant associations pointing to wnt/{beta}-catenin, TGF-{beta} and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

genetics↗

bioRxiv2017

Genome-wide Association Study Links APOEϵ4 and BACE1 Variants with Plasma Amyloid β Levels

INTRODUCTIONThere is increasing interest in plasma A{beta} as an endophenotype and biomarker of Alzheimers disease (AD). Identifying the genetic determinants of plasma A{beta} levels may elucidate important processes that determine plasma A{beta} measures. METHODSWe included 12,369 non-demented participants derived from eight population-based studies. Imputed genetic data and plasma A{beta}1-40, A{beta}1-42 levels and A{beta}1-42/A{beta}1-40 ratio were used to perform genome-wide association studies, gene-based and pathway analyses. Significant variants and genes were followed-up for the association with PET A{beta} deposition and AD risk. RESULTSSingle-variant analysis identified associations across APOE for A{beta}1-42 and A{beta}1-42/A{beta}1-40 ratio, and BACE1 for A{beta}1-40. Gene-based analysis of A{beta}1-40 additionally identified associations for APP, PSEN2, CCK and ZNF397. There was suggestive interaction between a BACE1 variant and APOE{varepsilon}4 on brain A{beta} deposition. DISCUSSIONIdentification of variants near/in known major A{beta}-processing genes strengthens the relevance of plasma-A{beta} levels both as an endophenotype and a biomarker of AD.

genetics↗