{"doi":"10.3389/fgene.2023.1075824","title":"Predicting late-stage age-related macular degeneration by integrating marginally weak SNPs in GWA studies","abstract":"Introduction: Age-related macular degeneration (AMD) is a progressive neurodegenerative disease and the leading cause of blindness in developed countries. Current genome-wide association studies (GWAS) for late-stage age-related macular degeneration are mainly single-marker-based approaches, which investigate one Single-Nucleotide Polymorphism (SNP) at a time and postpone the integration of inter-marker Linkage-disequilibrium (LD) information in the downstream fine mappings. Recent studies showed that directly incorporating inter-marker connection/correlation into variants detection can help discover novel marginally weak single-nucleotide polymorphisms, which are often missed in conventional genome-wide association studies, and can also help improve disease prediction accuracy. Methods: Single-marker analysis is performed first to detect marginally strong single-nucleotide polymorphisms. Then the whole-genome linkage-disequilibrium spectrum is explored and used to search for high-linkage-disequilibrium connected single-nucleotide polymorphism clusters for each strong single-nucleotide polymorphism detected. Marginally weak single-nucleotide polymorphisms are selected via a joint linear discriminant model with the detected single-nucleotide polymorphism clusters. Prediction is made based on the selected strong and weak single-nucleotide polymorphisms. Results: Several previously identified late-stage age-related macular degeneration susceptibility genes, for example, BTBD16 , C3 , CFH , CFHR3 , HTARA1 , are confirmed. Novel genes DENND1B , PLK5 , ARHGAP45 , and BAG6 are discovered as marginally weak signals. Overall prediction accuracy of 76.8% and 73.2% was achieved with and without the inclusion of the identified marginally weak signals, respectively. Conclusion: Marginally weak single-nucleotide polymorphisms, detected from integrating inter-marker linkage-disequilibrium information, may have strong predictive effects on age-related macular degeneration. Detecting and integrating such marginally weak signals can help with a better understanding of the underlying disease-development mechanisms for age-related macular degeneration and more accurate prognostics.","journal":"Frontiers in Genetics","year":2023,"id":369969,"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":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9527,"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":1128851,"name":"Jipeng Zhang","orcid":"0000-0003-0263-2899","position":1,"is_corresponding":false},{"id":263119,"name":"Ying Ding","orcid":"0000-0003-1352-1000","position":2,"is_corresponding":false},{"id":91757,"name":"Heng Huang","orcid":"0000-0002-3483-8333","position":3,"is_corresponding":false},{"id":232101,"name":"Yanming Li","orcid":"0000-0002-8213-9166","position":4,"is_corresponding":false},{"id":109275,"name":"Wei Chen","orcid":"0000-0001-7196-8703","position":5,"is_corresponding":false},{"id":481478,"name":"Xueping Zhou","orcid":"0000-0003-1530-7999","position":0,"is_corresponding":true}],"reference_count":82,"raw_metadata":null,"created_at":"2026-07-19T01:15:32.670954Z","pmid":"37065470","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":[]}