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An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease

BACKGROUND: The X chromosome is often omitted in disease association studies despite containing thousands of genes which may provide insight into well-known sex differences in the risk of Alzheimer’s Disease. OBJECTIVE: To model the expression of X chromosome genes and evaluate their impact on Alzhe...

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Autores principales: Zhang, Xueyi, Gomez, Lissette, Below, Jennifer, Naj, Adam, Martin, Eden, Kunkle, Brian, Bush, William S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274627/
https://www.ncbi.nlm.nih.gov/pubmed/37333116
http://dx.doi.org/10.1101/2023.06.06.543877
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author Zhang, Xueyi
Gomez, Lissette
Below, Jennifer
Naj, Adam
Martin, Eden
Kunkle, Brian
Bush, William S.
author_facet Zhang, Xueyi
Gomez, Lissette
Below, Jennifer
Naj, Adam
Martin, Eden
Kunkle, Brian
Bush, William S.
author_sort Zhang, Xueyi
collection PubMed
description BACKGROUND: The X chromosome is often omitted in disease association studies despite containing thousands of genes which may provide insight into well-known sex differences in the risk of Alzheimer’s Disease. OBJECTIVE: To model the expression of X chromosome genes and evaluate their impact on Alzheimer’s Disease risk in a sex-stratified manner. METHODS: Using elastic net, we evaluated multiple modeling strategies in a set of 175 whole blood samples and 126 brain cortex samples, with whole genome sequencing and RNA-seq data. SNPs (MAF>0.05) within the cis-regulatory window were used to train tissue-specific models of each gene. We apply the best models in both tissues to sex-stratified summary statistics from a meta-analysis of Alzheimer’s disease Genetics Consortium (ADGC) studies to identify AD-related genes on the X chromosome. RESULTS: Across different model parameters, sample sex, and tissue types, we modeled the expression of 217 genes (95 genes in blood and 135 genes in brain cortex). The average model R(2) was 0.12 (range from 0.03 to 0.34). We also compared sex-stratified and sex-combined models on the X chromosome. We further investigated genes that escaped X chromosome inactivation (XCI) to determine if their genetic regulation patterns were distinct. We found ten genes associated with AD at p 0.05, with only ARMCX6 in female brain cortex (p = 0.008) nearing the significance threshold after adjusting for multiple testing (α = 0.002). CONCLUSIONS: We optimized the expression prediction of X chromosome genes, applied these models to sex-stratified AD GWAS summary statistics, and identified one putative AD risk gene, ARMCX6.
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spelling pubmed-102746272023-06-17 An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease Zhang, Xueyi Gomez, Lissette Below, Jennifer Naj, Adam Martin, Eden Kunkle, Brian Bush, William S. bioRxiv Article BACKGROUND: The X chromosome is often omitted in disease association studies despite containing thousands of genes which may provide insight into well-known sex differences in the risk of Alzheimer’s Disease. OBJECTIVE: To model the expression of X chromosome genes and evaluate their impact on Alzheimer’s Disease risk in a sex-stratified manner. METHODS: Using elastic net, we evaluated multiple modeling strategies in a set of 175 whole blood samples and 126 brain cortex samples, with whole genome sequencing and RNA-seq data. SNPs (MAF>0.05) within the cis-regulatory window were used to train tissue-specific models of each gene. We apply the best models in both tissues to sex-stratified summary statistics from a meta-analysis of Alzheimer’s disease Genetics Consortium (ADGC) studies to identify AD-related genes on the X chromosome. RESULTS: Across different model parameters, sample sex, and tissue types, we modeled the expression of 217 genes (95 genes in blood and 135 genes in brain cortex). The average model R(2) was 0.12 (range from 0.03 to 0.34). We also compared sex-stratified and sex-combined models on the X chromosome. We further investigated genes that escaped X chromosome inactivation (XCI) to determine if their genetic regulation patterns were distinct. We found ten genes associated with AD at p 0.05, with only ARMCX6 in female brain cortex (p = 0.008) nearing the significance threshold after adjusting for multiple testing (α = 0.002). CONCLUSIONS: We optimized the expression prediction of X chromosome genes, applied these models to sex-stratified AD GWAS summary statistics, and identified one putative AD risk gene, ARMCX6. Cold Spring Harbor Laboratory 2023-10-05 /pmc/articles/PMC10274627/ /pubmed/37333116 http://dx.doi.org/10.1101/2023.06.06.543877 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Zhang, Xueyi
Gomez, Lissette
Below, Jennifer
Naj, Adam
Martin, Eden
Kunkle, Brian
Bush, William S.
An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease
title An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease
title_full An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease
title_fullStr An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease
title_full_unstemmed An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease
title_short An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease
title_sort x chromosome transcriptome wide association study implicates armcx6 in alzheimer’s disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274627/
https://www.ncbi.nlm.nih.gov/pubmed/37333116
http://dx.doi.org/10.1101/2023.06.06.543877
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