Browsing by Author "Yang, Zikun"

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    A multiethnic transcriptome for Alzheimer Disease identifies cross‐ancestry and ancestry‐specific expression profiles
    (Wiley, 2025-01-03) Yang, Zikun; Cieza, Basilio; Reyes-Dumeyer, Dolly; Lee, Annie J.; Dugger, Brittany N.; Jin, Lee-Way; Murray, Melissa E.; Dickson, Dennis W.; Pericak-Vance, Margaret A.; Vance, Jeffery M.; Foroud, Tatiana M.; Teich, Andrew F.; Mayeux, Richard; Tosto, Giuseppe; Neurology, School of Medicine
    Background: Alzheimer’s Disease (AD) presents complex molecular heterogeneity, influenced by a variety of factors including heterogeneous phenotypic, genetic, and neuropathologic presentations. Regulation of gene expression mechanisms is a primary interest of investigations aiming to uncover the underlying disease mechanisms and progression. Method: We generated bulk RNA‐sequencing in prefrontal cortex from 565 AD brain samples (non‐Hispanic Whites, n = 399; Hispanics, n = 113; African American, n = 12) across six U.S. brain banks, and conducted differential gene expression and enrichment analyses. We sought to identify cross‐ancestry and ancestry‐specific differentially expressed genes (DEG) and pathways across Braak stages, adjusting for sex, age at death, and RNA quality metrics. We validated our findings using the Religious Orders Study/Memory and Aging Project study (ROS/MAP, n = 1,095). Lastly, we validated top DEG using publically‐available human single‐nucleus RNA sequencing (snRNAseq) data. Result: AD‐known genes VGF (LFC = ‐0.661, padj = 3.78) and ADAMTS2 (padj = 1.21) were consistently differentially expressed across statistical models, ethnic groups, and replicated in ROS/MAP (Figure 1). Genes from the heat shock protein (HSP) family, e.g. HSPB7 (padj = 3.78), were the top DEG, also replicated in ROS/MAP. Ethnic‐stratified analyses prioritized TNFSF14 and SPOCD1 as top DEG in Hispanic samples. Gene set enrichment analysis highlighted several significantly pathways, including “TYROBP causal network in microglia” (WP3945; padj = 1.68) and “Alzheimer Disease” (WP5124; padj = 4.24). snRNAseq validated several DEG, including VGF downregulated in neurons (padj = 1.1). Conclusion: To our knowledge, this is the largest diverse transcriptome study for AD in post‐mortem tissue. We identified perturbated genes and pathways resulting in cross‐ethnic and ethnic‐specific findings, ultimately highlighting the importance of diversity in AD investigations.
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    Polytranscriptomic risk score for Alzheimer Disease in a large diverse multi‐center brain bank study
    (Wiley, 2025-01-03) Cieza, Basilio; Yang, Zikun; Reyes-Dumeyer, Dolly; Lee, Annie J.; Dugger, Brittany N.; Jin, Lee-Way; Murray, Melissa E.; Dickson, Dennis W.; Pericak-Vance, Margaret A.; Vance, Jeffery M.; Foroud, Tatiana M.; Mayeux, Richard; Tosto, Giuseppe; Neurology, School of Medicine
    Background: Alzheimer’s disease (AD) missing heritability remains extensive despite numerous genetic risk loci identified by genome‐wide association or sequencing studies. This has been attributed, at least partially, to mechanisms not currently investigated by traditional single‐marker/gene approaches. Polygenic Risk Scores (PRS) aggregate sparse genetic information across the genome to identify individual genetic risk profiles for disease prediction and patient risk stratification. Recent advancements have pivoted on innovative approaches utilizing OMICS data to construct such risk scores. Method: We employed a random forest algorithm to identify a list of gene candidates from bulk RNA sequencing data in prefrontal cortex from 565 AD brain samples (non‐Hispanic Whites, n = 399; Hispanics, n = 113; African American, n = 12) across six U.S. brain banks. Subsequently, we calculated their effect size on Braak staging using regression models to construct a polytranscriptomic risk score (PTRS). We employed two distinct models: “Ethnicity‐Agnostic” Model (randomly assigning samples to training and testing samples) and “Ethnicity‐Aware” Model (assigning NHW samples to training and Hispanics to testing sample). Analysis of variance and the receiver operating characteristics area under the curve (ROC AUC) was used to evaluate PTRS’s classification performances. We validated findings using the Religious Orders Study/Memory and Aging Project study (ROS/MAP, n = 1,095). Result: We found a significant difference in PTRS between samples with low vs. high Braak stages (≤4 vs. ≥5, p = 1*E‐04; Figure 1 upper panel). AUC was found to be 79‐81%, consistently in both Ethnicity‐Agnostic and Ethnicity‐Aware models (Figure 1 lower panel). Finally, the PTRS in ROS/MAP yielded a similar classification performance (p = 2*E‐04, AUC = 77%). Conclusion: Contrary to prior studies, we developed a PTRS with optimal transferability across ethnicities. This underscores the importance of developing novel tools to stratify and harmonize large brain repositories for AD.