{"doi":"10.1101/2023.06.06.543877","title":"An X Chromosome Transcriptome Wide Association Study Implicates ARMCX6 in Alzheimer’s Disease","abstract":"Abstract 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 .","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":408356,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9364,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":257281,"name":"Lissette Gomez","orcid":null,"position":1,"is_corresponding":false},{"id":16108,"name":"Jennifer E. Below","orcid":"0000-0002-6372-6402","position":2,"is_corresponding":false},{"id":54608,"name":"Adam C. Naj","orcid":"0000-0002-9621-2942","position":3,"is_corresponding":false},{"id":40736,"name":"Eden R. Martin","orcid":"0000-0002-4035-9152","position":4,"is_corresponding":false},{"id":256051,"name":"Brian W. Kunkle","orcid":"0000-0002-9515-5157","position":5,"is_corresponding":false},{"id":261839,"name":"William S. Bush","orcid":"0000-0002-9729-6519","position":6,"is_corresponding":false},{"id":1187646,"name":"Xueyi Zhang","orcid":"0000-0002-1834-2311","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T01:21:18.414003Z","pmid":"37333116","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}