Frontiers in Aging NeuroscienceNeurosciencePeer-reviewed journal article
Sex-Specific Cross Tissue Meta-Analysis Identifies Immune Dysregulation in Women with Alzheimer's Disease
Manish D. ParanjpeiD, Stella A. BelonwuiD, Jason K Wang, Tomiko OskotskyiD, Aarzu Gupta, Alice L. Taubes, Kelly A. ZalocuskyiD, Ishan ParanjpeiD, Benjamin Scott GlicksbergiD, Yadong HuangiD, Marina SirotaiD, Alzheimer’s Disease Neuroimaging Initiative
Abstract
In spite of evidence of females having a greater lifetime risk of developing Alzheimers Disease (AD) and greater apolipoprotein E4-related (apoE4) AD risk compared to males, molecular signatures underlying these findings remain elusive. We took a meta-analysis approach to study gene expression in the brains of 1,084 AD patients and age-matched controls and whole blood from 645 AD patients and age-matched controls. Gene-expression, network-based analysis and cell type deconvolution approaches revealed a consistent immune signature in the brain and blood of female AD patients that was absent in males. Machine learning-based classification of AD using gene expression from whole blood in addition to clinical features revealed an improvement in classification accuracy upon stratifying by sex, achieving an AUROC of 0.91 for females and 0.80 for males. These results help identify sex and apoE4 genotype-specific transcriptomic signatures of AD and underscore the importance of considering sex in the development of biomarkers and therapeutic strategies for AD.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 49
- FWCI
- 6.79
- Field percentile
- top 2%
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