{"doi":"10.1101/2021.08.13.21261887","title":"Genome Wide Analysis Across Alzheimer’s Disease Endophenotypes: Main Effects and Stage Specific Interactions","abstract":"ABSTRACT Introduction Genetic association analysis of key Alzheimer’s disease (AD) endophenotypes may provide insight into molecular mechanisms and genetic contributions. Methods Major AD endophenotypes based on the A/T/N (Amyloid-β, Tau, and Neurodegeneration) biomarkers and cognitive performance were selected from Alzheimer’s Disease Neuroimaging Initiative (ADNI) in up to 1,565 subjects. Genome-wide association analysis of quantitative phenotypes was performed using a main SNP effect and a SNP by Diagnosis interaction (SNPxDX) model to identify stage specific genetic effects. Results Sixteen novel or replicated loci were identified in the main effect model, with six ( SRSF10, MAPT, XKR3, KIAA1671, ZNF826P , and LOC100507506 ) meeting study significance thresholds with the A/T/N biomarkers. The SNPxDX model identified three study significant genetic loci ( BACH2, EP300, PACRG-AS1 ) associated with a neuroprotective effect in later AD stage endophenotypes. Discussion An endophenotype approach identified novel genetic associations and new insights into the associations that may otherwise be missed using conventional case-control models.","journal":"medRxiv","year":2021,"id":221455,"datarank":0.12726818450225963,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.023296107418267833,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.023296107418267833,"corpus_percentile":28.98584358319796,"corpus_rank":9181,"citation_count":1,"citer_count":1,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.711,"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":53300,"name":"Kwangsik Nho","orcid":"0000-0002-7624-3872","position":1,"is_corresponding":false},{"id":53156,"name":"Shannon L. Risacher","orcid":"0000-0002-3304-7943","position":2,"is_corresponding":false},{"id":324302,"name":"Sujuan Gao","orcid":"0000-0002-6741-6380","position":3,"is_corresponding":false},{"id":49224,"name":"Li Shen","orcid":"0000-0002-5443-0503","position":4,"is_corresponding":false},{"id":40730,"name":"Tatiana Foroud","orcid":"0000-0002-5549-2212","position":5,"is_corresponding":false},{"id":27595,"name":"Andrew J. Saykin","orcid":"0000-0002-1376-8532","position":6,"is_corresponding":false},{"id":243718,"name":"for the Alzheimer’s Disease Neuroimaging Initiative","orcid":null,"position":7,"is_corresponding":false},{"id":822018,"name":"Tanner Y. Jacobson","orcid":null,"position":0,"is_corresponding":true}],"reference_count":39,"raw_metadata":null,"created_at":"2026-07-18T23:53:55.215284Z","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":[]}