Brain network localization and transcriptomic decoding in subjective cognitive decline
Poster No:
143
Submission Type:
Abstract Submission
Authors:
Huan Lan1, Wenxiong Liu1, Song Wang1, Graham Kemp2, Xueling Suo1, Qiyong Gong1,3
Institutions:
1Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China, 2Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom, 3Xiamen Key Lab of Psychoradiology and Neuromodulation, Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, China
First Author:
Huan Lan
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University
Chengdu, China
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University
Chengdu, China
Co-Author(s):
Wenxiong Liu
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University
Chengdu, China
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University
Chengdu, China
Song Wang
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University
Chengdu, China
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University
Chengdu, China
Graham Kemp
Institute of Life Course and Medical Sciences, University of Liverpool
Liverpool, United Kingdom
Institute of Life Course and Medical Sciences, University of Liverpool
Liverpool, United Kingdom
Xueling Suo
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University
Chengdu, China
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University
Chengdu, China
Qiyong Gong
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University|Xiamen Key Lab of Psychoradiology and Neuromodulation, Department of Radiology, West China Xiamen Hospital of Sichuan University
Chengdu, China|Xiamen, China
Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University|Xiamen Key Lab of Psychoradiology and Neuromodulation, Department of Radiology, West China Xiamen Hospital of Sichuan University
Chengdu, China|Xiamen, China
Introduction:
As the population ages, the issue of dementia is growing more critical. Subjective cognitive decline (SCD), defined by self-reported cognitive deficits in the absence of measurable neuropsychological impairments, is regarded as a prodromal phase of Alzheimer's disease (AD) (Jessen et al., 2014). Individuals with SCD are at an increased risk of progressing to objective cognitive impairment and dementia, often associated with early AD-related pathology (Slot et al., 2019). Over the past decade, various neuroimaging studies have sought to identify the neural substrates of SCD, but findings have been inconsistent. A growing body of research suggests that neurodegenerative conditions might be better understood through brain networks rather than isolated brain areas (Fox, 2018). In this context, coordinate network mapping (CNM) has emerged as a promising tool for mapping the spatial distribution of various abnormal patterns into a common brain network that is disease- or symptom-specific (Darby et al., 2019; Younger et al., 2023). Consequently, this study aimed to identify whether the heterogeneous neuroimaging findings of SCD could be localized to a common brain network and to establish its associations with the transcriptome profiles. Additionally, we performed a traditional activation likelihood estimation (ALE) meta-analysis.
Methods:
We conducted a systematic literature review to identify studies that reported structural and resting-state functional brain abnormalities in individuals with SCD. Using a large, publicly normative connectome database comprising 1,000 subjects (Holmes et al., 2015), we mapped the common brain networks that were functionally connected to reported neuroimaging coordinates. Combined with the Allen Human Brain Atlas (Hawrylycz et al., 2012), we then employed transcription-neuroimaging spatial correlation and the ensemble-based gene category enrichment analysis to identify gene categories with expression related to the common networks in SCD, adhering to the recommended pipeline. Finally, to validate the robustness of the findings, we repeated the CNM analyses with an independent validation dataset comprising 308 healthy adults. These participants were recruited from local universities and communities through poster advertisements, and all provided written informed consent. Additionally, we used GingerALE, version 3.0.2 for traditional meta-analyses.
Results:
We included 45 studies comprising 2453 SCD patients and 3017 healthy controls. The identified structural network contains a wide distribution of brain regions, primarily including the bilateral precentral and postcentral gyrus, paracentral lobule, superior and middle temporal gyrus and right hippocampus, largely located in the somatosensory network (SMN). The identified functional network consisted of a set of brain regions centred on the parahippocampus and precuneus, mainly in the default mode network (DMN) (Figure 1). In the transcriptomic analysis, the identified structural network did not pass the Moran test (Pmoran = 0.2272). The functional network was colocalized with brain-wide gene expression involved in biological processes related to synaptic structure, calcium ion binding, cellular metabolism (Figure 2). In the validation analysis, we found that the spatial distribution of the resulting networks closely matched those identified in the large dataset, yet their spatial extent was more limited. In the ALE analyses, structural studies revealed significant atrophy in the left transverse temporal gyrus, no significant clusters were identified in the functional studies.
·Figure 1. The identified SCD-related networks
·Figure 2. Transcriptional profiles associated with SCD functional network map
Conclusions:
Our study help reconcile the seemingly irreproducible neuroimaging reports of SCD, highlighting the involvement of DMN and SMN from a network perspective, and further elucidated the associated transcriptomic signatures. This comprehensive understanding of the neurobiological mechanisms underlying SCD may contribute to identifying potential targets for early interventions.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Genetics:
Transcriptomics
Learning and Memory:
Long-Term Memory (Episodic and Semantic)
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Anatomy and Brain Mapping
Keywords:
Aging
FUNCTIONAL MRI
Memory
Meta- Analysis
Neurological
Phenotype-Genotype
STRUCTURAL MRI
Other - subjective cognitive decline; gene expression
1|2Indicates the priority used for review
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Provide references using APA citation style.
Fox, M. D. (2018). Mapping Symptoms to Brain Networks with the Human Connectome. New England Journal of Medicine, 379(23), 2237-2245.
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Slot, R. E. R., Sikkes, S. A. M., Berkhof, J., Brodaty, H., Buckley, R., Cavedo, E., Dardiotis, E., Guillo-Benarous, F., Hampel, H., Kochan, N. A., Lista, S., Luck, T., Maruff, P., Molinuevo, J. L., Kornhuber, J., Reisberg, B., Riedel-Heller, S. G., Risacher, S. L., Roehr, S.,…van der Flier, W. M. (2019). Subjective cognitive decline and rates of incident Alzheimer's disease and non-Alzheimer's disease dementia. Alzheimer's & Dementia: The Journal of the Alzheimer's Association, 15(3), 465-476.
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