Chrome Extension
WeChat Mini Program
Use on ChatGLM

Genes That Escape X Chromosome Inactivation Are Associated with Alzheimer’s Disease Endophenotypes: Findings from ROSMAP

Alzheimer's &amp Dementia(2024)

Vanderbilt Memory &amp Alzheimer’s Center | Massachusetts General Hospital | Harvard Medical School | Massachusetts General HospitalHarvard Medical School | Vanderbilt Genetics Institute | Columbia University Irving Medical Center | Rush Alzheimer’s Disease Center | Rush Alzheimer's Disease Center | Vanderbilt Memory and Alzheimer’s Center

Cited 0|Views0
Abstract
AbstractBackgroundWomen are disproportionately affected by Alzheimer’s disease (AD) and exhibit greater AD neuropathology than men. Women possess two X chromosomes, with one randomly silenced across each cell for dosage compensation. X chromosome inactivation (XCI) is not complete, and XCI‐escaping genes provide a promising avenue of discovery for biological pathways driving sex‐specific AD risk. Our objective was to examine XCI‐escaping genes in association with β‐amyloid (Aβ) and tau tangle density, and cognitive decline.MethodsUsing bulk RNAseq from dorsolateral prefrontal cortex tissue, Aβ plaque and tau tangle pathology, and antemortem longitudinal cognition data from ROSMAP, we investigated whether XCI‐escaping genes explain significant variance in AD endophenotypes. Propensity scoring based on age‐at‐death, postmortem interval, race, latency‐to‐death, education, and APOEε4 status resulted in a matched sample (N = 648, age‐at‐deathmean(SD) = 87.5(6.5)). Linear regression and mixed‐effects models assessed the association between 216 reported XCI‐escaping genes and Aβ and tau at autopsy, and a longitudinal global cognitive composite. Analyses were sex‐stratified and FDR‐corrected. Differential expression analyses assessed sex‐biased mean gene expression.Results22 XCI‐escaping genes were associated with Aβ (20 female‐specific, 2 male‐specific), 49 genes with tau (43 female‐specific, 6 male‐specific), and 48 genes with cognitive decline (46 female‐specific, 2 male‐specific). In women, 40%(8/20) were negatively associated with Aβ, 56%(24/43) negatively associated with tauopathy, and 43%(20/46) were negatively associated with cognitive decline. Of note, higher GRIPAP1 expression was associated with lower Aβ (β = ‐0.18, pFDR = 0.02) and tau (β = ‐0.21, pFDR = 0.001), and slower cognitive decline (β = 0.02, pFDR = 0.04) in women. By contrast, ATP11C expression was associated with higher Aβ (β = 0.19, pFDR = 0.03) and tau (β = 0.15, pFDR = 0.03), and faster cognitive decline (β = ‐0.02, pFDR = 0.03) in women. Unexpectedly, of 216 XCI‐escaping genes tested, only 4% were expressed more highly in females than males.ConclusionGRIPAP1 and ATP11C are implicated in endosomal recycling and inflammation, respectively, supporting two pathways associated with AD. Both GRIPAP1 and ATP11C exhibited sex‐parity in gene expression suggesting that single‐cell RNAseq will be necessary to further characterize XCI‐escapism in relation to AD risk. Altogether, this study presents evidence that studying the X chromosome is integral to understanding female resistance, resilience, and vulnerability to AD pathology.
More
Translated text
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest