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Zhu, D. C.

Publications and source records attributed to Zhu, D. C..

3 recordsLinked to original sources

Multimodal MRI Clustering Reveals an Elevated Free-Water Biotype in Autism with Increased Social Symptoms

Background: Autism spectrum disorder (ASD) is neurobiologically heterogeneous, and group comparisons may mask effects confined to subgroups. We tested whether distinct biotypes exist within ASD using unsupervised clustering of multimodal MRI. Methods: We analyzed 149 participants with ASD and 129 typically developing (TD) controls from the Autism Brain Imaging Data Exchange II (6 sites; age 5 to 64 years). Site-harmonized features comprised free water (FW), tissue anisotropy and diffusivity, diffusion tensor image analysis along the perivascular space (DTI-ALPS), cerebrospinal fluid (CSF) volumes and exploratory resting-state regional homogeneity. ASD participants were clustered with k-means using global (7 features) and regional (17 features) sets, with robustness tested by permutation and two further algorithms. TD participants were projected post hoc to test specificity. A composite imaging score was related to Social Responsiveness Scale (SRS) subscales, symptom severity and IQ using partial correlations with false discovery rate correction. Results: Clustering identified an elevated free-water (EFW) biotype comprising approximately 10% of ASD participants, defined by markedly increased FW (d = +4.91 versus remaining ASD participants), reduced tissue anisotropy, reduced DTI-ALPS and enlarged ventricles. It was recovered across feature sets and algorithms (permutation p < .0001) and departed from TD norms, unlike the remaining ASD participants. The composite score correlated with social-perceptual and communicative SRS subscales, most strongly social awareness (r = +0.253, q = .026), but not with symptom severity or IQ. FW related to social motivation in children and adolescents (r = +0.287, q = .037) but not adults. Limitations: Each person was scanned once, so we cannot tell whether these brain differences cause social difficulties or how they change with age. The subgroup was small, clinical data were incomplete, the sample was mostly male with a wide age range, and the findings await confirmation in an independent group. Free water can reflect inflammation, swelling or tissue loss, so its biological meaning remains uncertain. Conclusions: We identify an ASD subgroup defined by extracellular fluid excess and altered white matter that is associated with greater social difficulties. If replicated, this signature may help stratify autistic individuals in mechanistic studies and clinical trials.

neuroscience↗

A Functional Resting-State Network Atlas Based on 420 Older Adults with Hypertension

The Risk Reduction for Alzheimers Disease (rrAD) trial included 513 cognitively normal, sedentary, hypertensive older adults (aged 60 to 85 years) with dementia risk factors. We utilized 420 high-quality baseline resting-state functional MRI (rs-fMRI) scans from this cohort to develop a functional atlas tailored for aging populations. Typical rs-fMRI atlases derived from healthy young adults do not account for age-related changes, such as cortical atrophy, enlarged ventricles, and altered connectivity. To address this gap, we created a cohort-specific MNI-adjacent anatomical template, rrAD420, using SPM12s DARTEL registration. In this space, we derived a comprehensive functional atlas using both group independent component analysis (GICA) and probabilistic functional mode decomposition (PROFUMO). The rrAD420 atlas offers detailed representations of Resting-State Network (RSN) connectivity, encompassing unique configurations and overlapping interactions. It features two Default-Mode Network (DMN)-specific seed-based maps (DMN24 with cerebellum, DMN18 without) and data-driven components resembling the major RSNs. Furthermore, PROFUMO allowed for the identification of multimodal and combinatory networks, capturing connections within and between RSNs. While optimized for hypertensive older adults, the rrAD420 atlas serves as a versatile tool for broader aging populations, aiding in the study of neurodegenerative processes and biomarker discovery.

neuroscience↗

Novel inductively-coupled ear-bars (ICEs) for fMRI signal enhancement in rat entorhinal cortex

Entorhinal cortex (EC) is a potential target of deep brain stimulation in Alzheimers disease (AD) and fMRI can enable whole-brain dynamic mapping noninvasively. However, it remains challenging to study EC-based fMRI connectivity in rodents due to image signal loss and the lower sensitivity of the surface coil ring or array coil for deep brain areas. To reduce the magnetic susceptibility artifacts driven signal loss issue, we introduced baby cream into the middle ear. To improve detection sensitivity, we implemented novel inductively-coupled ear-bars (ICEs) in the 7 T Bruker scanner, which resulted in an approximately 2-fold signal-to-noise ratio (SNR) increase in EC over the conventional surface array. The ICE can be conveniently utilized as an add-on device, with no modulation to the scanner interface. To demonstrate the applicability of ICEs for both task and resting-state (rs) fMRI, whole-brain echo-planar imaging (EPI) was performed in anesthetized rats modeling AD mixed dementia. Seed-based rs-fMRI connectivity maps emanating from the left entorhinal cortex demonstrated its connectivity to the hippocampus, piriform cortex, septal nuclei, and prefrontal cortex. Hence, this work demonstrates an optimized procedure for ICE by acquiring large scale networks emanating from a seed region that was not easily accessible by conventional MRI detectors, enabling better observation of EC-based brain fMRI connectivity studies with a higher signal-to-noise ratio in rodent models of dementia.

neuroscience↗