{"id":"https://openalex.org/W7116799906","doi":"https://doi.org/10.1186/s13040-025-00506-0","title":"Cross-cohort genetic risk prediction for Alzheimer\u2019s disease: a transfer learning approach using GWAS and deep learning models","display_name":"Cross-cohort genetic risk prediction for Alzheimer\u2019s disease: a transfer learning approach using GWAS and deep learning models","publication_year":2025,"publication_date":"2025-12-22","ids":{"openalex":"https://openalex.org/W7116799906","doi":"https://doi.org/10.1186/s13040-025-00506-0","pmid":"https://pubmed.ncbi.nlm.nih.gov/41430307"},"language":"en","primary_location":{"id":"doi:10.1186/s13040-025-00506-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-025-00506-0","pdf_url":"https://link.springer.com/content/pdf/10.1186/s13040-025-00506-0.pdf","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1186/s13040-025-00506-0.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056427557","display_name":"Isibor Kennedy Ihianle","orcid":"https://orcid.org/0000-0001-7445-8573"},"institutions":[{"id":"https://openalex.org/I52590639","display_name":"Nottingham Trent University","ror":"https://ror.org/04xyxjd90","country_code":"GB","type":"education","lineage":["https://openalex.org/I52590639"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Isibor Kennedy Ihianle","raw_affiliation_strings":["Nottingham Trent University, Nottingham, NG11 8NS, UK. isibor.ihianle@ntu.ac.uk"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nottingham Trent University, Nottingham, NG11 8NS, UK. isibor.ihianle@ntu.ac.uk","institution_ids":["https://openalex.org/I52590639"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121003820","display_name":"Wathsala Samarasekara","orcid":null},"institutions":[{"id":"https://openalex.org/I52590639","display_name":"Nottingham Trent University","ror":"https://ror.org/04xyxjd90","country_code":"GB","type":"education","lineage":["https://openalex.org/I52590639"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wathsala Samarasekara","raw_affiliation_strings":["Nottingham Trent University, Nottingham, NG11 8NS, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nottingham Trent University, Nottingham, NG11 8NS, UK","institution_ids":["https://openalex.org/I52590639"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120975292","display_name":"Keeley Brookes","orcid":null},"institutions":[{"id":"https://openalex.org/I52590639","display_name":"Nottingham Trent University","ror":"https://ror.org/04xyxjd90","country_code":"GB","type":"education","lineage":["https://openalex.org/I52590639"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Keeley Brookes","raw_affiliation_strings":["Nottingham Trent University, Nottingham, NG11 8NS, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nottingham Trent University, Nottingham, NG11 8NS, UK","institution_ids":["https://openalex.org/I52590639"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084576357","display_name":"Pedro Machado","orcid":"https://orcid.org/0000-0002-1697-1667"},"institutions":[{"id":"https://openalex.org/I52590639","display_name":"Nottingham Trent University","ror":"https://ror.org/04xyxjd90","country_code":"GB","type":"education","lineage":["https://openalex.org/I52590639"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pedro Machado","raw_affiliation_strings":["Nottingham Trent University, Nottingham, NG11 8NS, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nottingham Trent University, Nottingham, NG11 8NS, UK","institution_ids":["https://openalex.org/I52590639"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5056427557"],"corresponding_institution_ids":["https://openalex.org/I52590639"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.6260686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"1","first_page":"89","last_page":"89"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10261","display_name":"Genetic Associations and Epidemiology","score":0.777999997138977,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10261","display_name":"Genetic Associations and Epidemiology","score":0.777999997138977,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11642","display_name":"Genomics and Rare Diseases","score":0.04569999873638153,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.03590000048279762,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7163000106811523},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6531000137329102},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46950000524520874},{"id":"https://openalex.org/keywords/knowledge-transfer","display_name":"Knowledge transfer","score":0.46059998869895935},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.44679999351501465},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.42809998989105225},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42340001463890076},{"id":"https://openalex.org/keywords/genome-wide-association-study","display_name":"Genome-wide association study","score":0.3968000113964081}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7513999938964844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.746999979019165},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.722000002861023},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7163000106811523},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6531000137329102},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46950000524520874},{"id":"https://openalex.org/C2776960227","wikidata":"https://www.wikidata.org/wiki/Q2586354","display_name":"Knowledge transfer","level":2,"score":0.46059998869895935},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42340001463890076},{"id":"https://openalex.org/C106208931","wikidata":"https://www.wikidata.org/wiki/Q1098876","display_name":"Genome-wide association study","level":5,"score":0.3968000113964081},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.3885999917984009},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.3555999994277954},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3499999940395355},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.30970001220703125},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3057999908924103},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C2993967602","wikidata":"https://www.wikidata.org/wiki/Q5532932","display_name":"Genetic variants","level":4,"score":0.26989999413490295},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.2655999958515167}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1186/s13040-025-00506-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-025-00506-0","pdf_url":"https://link.springer.com/content/pdf/10.1186/s13040-025-00506-0.pdf","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},{"id":"pmid:41430307","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41430307","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData mining","raw_type":"Journal Article"},{"id":"pmh:oai:irep.ntu.ac.uk:54952","is_oa":false,"landing_page_url":"https://irep.ntu.ac.uk/id/eprint/54952/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400559","display_name":"Nottingham Trent University's Institutional Repository (Nottingham Trent Repository)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I52590639","host_organization_name":"Nottingham Trent University","host_organization_lineage":["https://openalex.org/I52590639"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:65f8cb7b052146d788690273b328acbe","is_oa":true,"landing_page_url":"https://doaj.org/article/65f8cb7b052146d788690273b328acbe","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BioData Mining, Vol 18, Iss 1, Pp 1-30 (2025)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12752400","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12752400/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BioData Min","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s13040-025-00506-0","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13040-025-00506-0","pdf_url":"https://link.springer.com/content/pdf/10.1186/s13040-025-00506-0.pdf","source":{"id":"https://openalex.org/S84409260","display_name":"BioData Mining","issn_l":"1756-0381","issn":["1756-0381"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioData Mining","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7116799906.pdf","grobid_xml":"https://content.openalex.org/works/W7116799906.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W2040288173","https://openalex.org/W2115779804","https://openalex.org/W2165698076","https://openalex.org/W2908002252","https://openalex.org/W2916749909","https://openalex.org/W2945957565","https://openalex.org/W2950886245","https://openalex.org/W2970480306","https://openalex.org/W2982184013","https://openalex.org/W2995918088","https://openalex.org/W2996501146","https://openalex.org/W2997842393","https://openalex.org/W3016001416","https://openalex.org/W3035903835","https://openalex.org/W3045873065","https://openalex.org/W3112948680","https://openalex.org/W3138717070","https://openalex.org/W3162782009","https://openalex.org/W3169406292","https://openalex.org/W3177252661","https://openalex.org/W3208670486","https://openalex.org/W3215388709","https://openalex.org/W4225961941","https://openalex.org/W4283593236","https://openalex.org/W4290710294","https://openalex.org/W4302426085","https://openalex.org/W4367598034","https://openalex.org/W4377103021","https://openalex.org/W4388573469","https://openalex.org/W4398208464","https://openalex.org/W4405758022","https://openalex.org/W4405915982","https://openalex.org/W4411541890"],"related_works":[],"abstract_inverted_index":{"Alzheimer\u2019s":[0],"Disease":[1],"(AD)":[2],"represents":[3],"a":[4,60,100,189,194],"growing":[5],"global":[6],"health":[7],"challenge,":[8],"driven":[9],"by":[10,27,113],"complex":[11,190],"genetic":[12,258],"factors":[13],"and":[14,66,76,80,138,146,220,228,237,252],"diverse":[15],"risk":[16,50,176,269],"contributors.":[17],"Currently,":[18],"an":[19],"estimated":[20],"55":[21],"million":[22],"people":[23],"worldwide":[24],"are":[25,233],"affected":[26],"dementia,":[28],"with":[29,59,132],"AD":[30,49,175,268],"responsible":[31],"for":[32],"60\u201370%":[33],"of":[34,42,74,93,125,148,170,186,231,244,249,256,264],"these":[35,126,149],"cases.":[36],"This":[37],"paper":[38],"explores":[39],"the":[40,72,123,143,168,184,211,254,261],"application":[41],"advanced":[43],"machine":[44],"learning":[45,65,128,154],"approaches":[46,129],"to":[47,87,102,119,193,210,235],"predict":[48],"using":[51],"Genome-Wide":[52],"Association":[53],"Studies":[54],"data":[55,162,171],"from":[56,116,188],"multiple":[57],"cohorts,":[58],"particular":[61],"focus":[62],"on":[63],"transfer":[64,153,185],"feature":[67],"selection":[68],"techniques.":[69],"We":[70],"evaluate":[71,142],"performance":[73,109,124],"Wide":[75],"Deep":[77],"Neural":[78],"Networks":[79],"Multi-Head":[81],"Attention":[82],"in":[83,110,173,217,223,240,267],"assessing":[84],"their":[85],"ability":[86],"generalise":[88],"across":[89,151],"datasets.":[90],"As":[91],"part":[92],"this,":[94],"we":[95,204],"explore":[96],"knowledge":[97,115,180,187],"distillation":[98,181],"as":[99,226],"strategy":[101],"enhance":[103,202],"model":[104,192,250],"efficiency":[105,147],"through":[106],"improved":[107],"generalisation":[108],"smaller":[111],"architectures":[112],"transferring":[114],"high-capacity":[117],"models":[118,150],"lightweight":[120],"ones.":[121],"Furthermore,":[122],"deep":[127],"is":[130],"compared":[131],"tree-based":[133],"ensembles,":[134],"including":[135],"Random":[136],"Forest":[137],"XGBoost.":[139],"Our":[140],"experiments":[141],"generalisability,":[144],"transferability,":[145],"different":[152],"scenarios.":[155],"Findings":[156],"indicate":[157],"that":[158],"aggregating":[159],"multi-cohort":[160],"training":[161],"significantly":[163,198],"enhances":[164],"predictive":[165],"performance,":[166],"highlighting":[167,221],"importance":[169,219],"diversity":[172],"improving":[174,199],"assessment.":[177],"The":[178,242],"proposed":[179],"approach":[182],"enables":[183,246],"teacher":[191],"simpler":[195],"student":[196,212],"model,":[197],"performance.":[200],"To":[201],"interpretability,":[203],"apply":[205],"SHAP":[206,245],"(SHapley":[207],"Additive":[208],"exPlanations)":[209],"models,":[213],"revealing":[214],"cohort-specific":[215],"differences":[216],"SNP":[218],"variants":[222],"genes":[224],"such":[225],"ABI3BP":[227],"SYN3,":[229],"both":[230],"which":[232],"linked":[234],"immune":[236],"synaptic":[238],"functions":[239],"AD.":[241],"integration":[243],"transparent":[247],"interpretation":[248],"decisions":[251],"supports":[253],"identification":[255],"transferable":[257],"markers,":[259],"reinforcing":[260],"clinical":[262],"relevance":[263],"our":[265],"framework":[266],"prediction.":[270]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-12-22T00:00:00"}