{"doi":"10.17615/xg4d-5d97","title":"Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits","abstract":"Structural variations of the human brain are heritable and highly polygenic traits, with hundreds of associated genes identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) can both prioritize these GWAS findings and also identify additional gene-trait associations. Here we perform cross-tissue TWAS analysis of 211 structural neuroimaging and discover 278 associated genes exceeding Bonferroni significance threshold of 1.04 × 10−8. The TWAS-significant genes for brain structures have been linked to a wide range of complex traits in different domains. Through TWAS gene-based polygenic risk scores (PRS) prediction, we find that TWAS PRS gains substantial power in association analysis compared to conventional variant-based GWAS PRS, and up to 6.97% of phenotypic variance (p-value = 7.56 × 10−31) can be explained in independent testing data sets. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.","journal":"UNC Libraries","year":2021,"id":229818,"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":0.8745,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":170815,"name":"X. Wang","orcid":null,"position":1,"is_corresponding":false},{"id":834841,"name":"Paula D.M. Sullivan","orcid":null,"position":2,"is_corresponding":false},{"id":155692,"name":"Y. Li","orcid":null,"position":3,"is_corresponding":false},{"id":27184,"name":"H. Zhao","orcid":"0000-0002-6638-847X","position":4,"is_corresponding":false},{"id":834842,"name":"Tianyuan Luo","orcid":null,"position":5,"is_corresponding":false},{"id":834843,"name":"Zeming Yu","orcid":null,"position":6,"is_corresponding":false},{"id":776186,"name":"Hongrui Zhu","orcid":"0000-0001-6823-6827","position":7,"is_corresponding":false},{"id":834844,"name":"Yong-Tao Shan","orcid":null,"position":8,"is_corresponding":false},{"id":834572,"name":"Bochuan Zhao","orcid":"0009-0008-6866-1717","position":9,"is_corresponding":false},{"id":834573,"name":"Yalin Yang","orcid":"0000-0001-7086-3440","position":10,"is_corresponding":false},{"id":834845,"name":"Tongxu Li","orcid":null,"position":11,"is_corresponding":false},{"id":56538,"name":"Z. Zhu","orcid":null,"position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-18T23:55:01.675482Z","pmid":null,"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":[]}