Biology subjects

Chen, C. L.-H.

Publications and source records attributed to Chen, C. L.-H..

7 recordsLinked to original sources

bioRxiv2024

WMH-DualTasker: A Dual-Task Deep Learning Model with Self-supervised Consistency for Automated Segmentation and Visual Rating of White matter Hyperintensities - a Multicentre study

BackgroundWhite matter hyperintensities (WMH) are neuroimaging markers linked to an elevated risk of cognitive decline. WMH severity is typically assessed via visual rating scales and through volumetric segmentation. While visual rating scales are commonly used in clinical practice, they offer limited descriptive power. In contrast, supervised volumetric segmentation requires manually annotated masks, which is labor-intensive and challenging to scale for large studies. Therefore, our goal was to develop an automated deep learning model that can provide accurate and holistic quantification of WMH severity with minimal supervision. MethodsWe developed WMH-DualTasker, a deep learning model that simultaneously performs voxel-wise segmentation and visual rating score prediction. The model employs self-supervised learning with transformation-invariant consistency constraints, using WMH visual ratings (ARWMC scale, range 0-30) from clinical settings as the sole supervisory signal. Additionally, we assessed its clinical utility by applying it to identify individuals with mild cognitive impairment (MCI) and to predict dementia conversion. FindingsThe volumetric quantification performance of WMH-DualTasker was either superior to or on par with existing supervised methods, as demonstrated on the MICCAI-WMH dataset (N=60, Dice=0.602) and the SINGER dataset (N=64, Dice=0.608). Furthermore, the model exhibited strong agreement with clinical visual rating scales on an external dataset (SINGER, MAE=1.880, K=0.77). Importantly, WMH severity metrics derived from WMH-DualTasker improved predictive performance beyond conventional clinical features for MCI classification (AUC=0.718, p<0.001), MCI conversion prediction (AUC=0.652, p<0.001) using the ADNI dataset. InterpretationsWMH-DualTasker substantially reduces the reliance on labor-intensive manual annotations, facilitating more efficient and scalable quantification of WMH severity in large-scale population studies. This innovative approach has the potential to advance preventive and precision medicine by enhancing the assessment and management of vascular cognitive impairment associated with WMH. Code and model weights are publicly available at https://github.com/hzlab/WMH-DualTasker.

neuroscience↗

bioRxiv2024

Additive effects of cerebrovascular disease functional connectome phenotype and plasma p-tau181 on longitudinal neurodegeneration and cognitive outcomes

INTRODUCTIONWe investigated the effects of multiple cerebrovascular disease (CeVD) neuroimaging markers on brain functional connectivity (FC), and how such CeVD-related FC changes interact with plasma p-tau181 (Alzheimers disease (AD) marker) to influence downstream neurodegeneration and cognitive changes. METHODSMultivariate associations between four CeVD markers and whole-brain FC in 529 participants across the dementia spectrum were examined using partial least squares correlation. Interactive effects of CeVD-related FC patterns and p-tau181 on longitudinal grey matter volume and cognitive changes were investigated using linear mixed-effects models. RESULTSWe identified a brain FC phenotype associated with high CeVD burden across all markers. Further, expression of this general CeVD-related FC phenotype and p-tau181 contributed additively, but not synergistically, to baseline and longitudinal grey matter volumes and cognitive changes. DISCUSSIONOur findings suggest that CeVD exerts global effects on the brain connectome and highlight the additive nature of AD and CeVD on neurodegeneration and cognition.

neuroscience↗

bioRxiv2023

Investigating the validity and interpretability of longitudinal brain age underlying cognition in Asian children and older adults

Brain age has emerged as a powerful tool to understand neuroanatomical aging and its link to health outcomes like cognition. However, there remains a lack of studies investigating the rate of brain aging and its relationship to cognition. Furthermore, most brain age models are trained and tested on cross-sectional data from primarily Caucasian, adult participants. It is thus unclear how well these models generalize to non-Caucasian participants, especially children. Here, we tested a previously published deep learning model on Singaporean elderly participants (55 - 88 years old) and children (4 - 11 years old). We found that the model directly generalized to the elderly participants, but model finetuning was necessary for children. After finetuning, we found that the rate of change in brain age gap was associated with future executive function performance in both elderly participants and children. We further found that lateral ventricles and frontal areas contributed to brain age prediction in elderly participants, while white matter and posterior brain regions were more important in predicting brain age of children. Taken together, our results suggest that there is potential for generalizing brain age models to diverse populations. Moreover, the longitudinal change in brain age gap reflects developing and aging processes in the brain, relating to future cognitive function.

neuroscience↗

bioRxiv2022

Intermittent Fasting Mitigates Vascular and Neuronal Pathologies in a Mouse Model of Vascular Dementia

Chronic cerebral hypoperfusion (CCH) is an important pathophysiological mechanism of vascular cognitive impairment (VCI). The heterogeneous effects of CCH complicate establishing single target therapies against VCI and its more severe form, vascular dementia (VaD). Intermittent fasting (IF) has multiple targets and is neuroprotective across a range of disease conditions including stroke, but its effects against CCH-induced neurovascular pathologies remain to be elucidated. We therefore assessed the effect of IF against CCH-associated neurovascular pathologies and investigated underlying mechanisms. Male C57BL/6 mice were subjected to either ad libitum feeding (AL) or IF (16 hours of fasting per day) for 4 months. In both groups, CCH was experimentally induced by the bilateral common carotid artery stenosis (BCAS) method. Sham operated groups were used as controls. Measures of leaky microvessels, blood brain barrier (BBB) permeability, protein expression of tight junctions, extracellular matrix components and white matter changes were determined to investigate the effect of IF against CCH-induced neurovascular pathologies. IF alleviated CCH-induced neurovascular pathologies by reducing the number of leaky microvessels, BBB breakdown, loss of tight junctional proteins and vascular endothelial growth factors. In addition, IF mitigated the severity of white matter lesions, maintained myelin basic protein levels, while concurrently reducing hippocampal neuronal cell death. Furthermore, IF reduced CCH-induced increase in levels of matrix metalloproteinase (MMP)-2 and its upstream activator MT1-MMP, which are involved in the breakdown of the extracellular matrix that is a core component of the BBB. Additionally, we observed that IF reduced CCH-induced increase in the oxidative stress marker malondialdehyde, and increased antioxidant markers glutathione and superoxide dismutase. Combined, our data suggests that IF attenuates neurovascular damage, metalloproteinase and oxidative stress-associated pathways, and cell death in the brain following CCH in a mouse model of VCI. Although IF has yet to be assessed in human patients with VaD, our data suggest that IF may be an effective means of preventing the onset or suppressing the development of neurovascular pathologies in VCI and VaD.

neuroscience↗

bioRxiv2020

Hippocampal Transcriptome Profiling Reveals Common Disease Pathways in Chronic Hypoperfusion and Ageing

Vascular dementia (VaD) is a progressive cognitive impairment of vascular etiology. VaD is characterized by cerebral hypoperfusion, increased blood-brain barrier permeability and white matter lesions. An increased burden of VaD is expected due to rapidly aging populations. The hippocampus is particularly susceptible to hypoperfusion, and the resulting memory impairment may play a crucial role in VaD. Here we have investigated the hippocampal gene expression profile of young and old mice subjected to chronic cerebral hypoperfusion by bilateral common carotid artery stenosis (BCAS). Our data in sham-operated young and aged mice show the normal age-associated decline in cerebral blood flow and differential gene expression. BCAS and ageing caused broadly similar effects, however, BCAS-induced changes in hippocampal gene expression differed between young and aged mice. Specifically, transcriptomic analysis indicated that in comparison to young sham mice, many pathways altered by BCAS in young mice resembled those present in sham aged mice. Immunoblot analyses confirmed these findings. Finally, relative to young sham mice the cell type-specific profile of genes in both young BCAS and old sham animals further revealed common cell-specific genes. Our data provide a genetic-based molecular framework for chronic hypoperfusion-induced hippocampal damage and reveal common cellular signaling pathways likely to be important in the pathophysiology of VaD.

neuroscience↗

bioRxiv2020

AIM2 Inflammasome Mediates Hallmark Neuropathological Alterations and Cognitive Impairment in a Mouse Model of Vascular Dementia

Chronic cerebral hypoperfusion is associated with vascular dementia (VaD). Cerebral hypoperfusion may initiate complex molecular and cellular inflammatory pathways that contribute to long-term cognitive impairment and memory loss. Here we used a bilateral common carotid artery stenosis (BCAS) mouse model of VaD to investigate its effect on the innate immune response - particularly the inflammasome signaling pathway. Comprehensive analyses revealed that chronic cerebral hypoperfusion induces a complex temporal expression and activation of inflammasome components and their downstream products (IL-1{beta} and IL-18) in different brain regions, and promotes activation of apoptotic and pyroptotic cell death pathways. Polarized glial cell activation, white matter lesion formation and hippocampal neuronal loss also occurred in a spatiotemporal manner. Moreover, in AIM2 knockout mice we observed attenuated inflammasome-mediated production of proinflammatory cytokines, apoptosis and pyroptosis, as well as resistance to chronic microglial activation, myelin breakdown, hippocampal neuronal loss, and behavioural and cognitive deficits following BCAS. Hence, we have demonstrated that activation of the AIM2 inflammasome substantially contributes to the pathophysiology of chronic cerebral hypoperfusion-induced brain injury and may therefore represent a promising therapeutic target for attenuating cognitive impairment in VaD.

neuroscience↗

bioRxiv2019

Dynamics of murine brain protein synthesis in vivo identify the hippocampus, cortex and cerebellum as highly active metabolic sites

Identification of proteins that are synthesized de novo in response to specific microenvironmental cues is critical to understanding the molecular mechanisms that underpin key physiological processes and pathologies. Here we report that a brief period of pulsed SILAC diet (Stable Isotope Labelling by Amino acids in Cell culture) enables determination of biological functions corresponding to actively translating proteins in the mouse brain. Our data demonstrate that the hippocampus, cortex and cerebellum are highly active sites of protein synthesis, rapidly expressing key mediators of nutrient sensing and lipid metabolism, as well as critical regulators of synaptic function, axon guidance, and circadian entrainment. Together, these findings confirm that protein metabolic activity varies significantly between brain regions in vivo and indicate that pSILAC-based approaches can identify specific anatomical sites and biological pathways likely to be suitable for drug targeting in neurodegenerative disorders.\n\nAbbreviationsApoA1: Apolipoprotein A1, ApoA4: Apolipoprotein A4, ApoE: Apolipoprotein E, ApoJ/Clu: Apolipoprotein J/Clusterin, App: Amyloid-{beta} precursor/A4 protein: App, HDL: high density lipoprotein, Lrp1: Low density lipoprotein receptor-related protein 1, pSILAC: pulsed SILAC, pSIVOM: pulsed-SILAC in vivo labelling in mouse, SILAC: Stable Isotope Labelling by Amino acids in Cell culture)

neuroscience↗