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000280043 037__ $$aDZNE-2025-00882
000280043 041__ $$aEnglish
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000280043 1001_ $$00000-0002-0531-6309$$aBracher-Smith, Matthew$$b0
000280043 245__ $$aMachine learning in Alzheimer's disease genetics.
000280043 260__ $$a[London]$$bSpringer Nature$$c2025
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000280043 520__ $$aTraditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer's disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk. We utilised Gradient Boosting Machines (GBMs), biological pathway-informed Neural Networks (NNs), and Model-based Multifactor Dimensionality Reduction (MB-MDR) models. ML approaches successfully captured all genome-wide significant genetic variants identified in the training set and 22% of associations from larger meta-analyses. They highlight 6 novel loci which replicate in an external dataset, including variants which map to ARHGAP25, LY6H, COG7, SOD1 and ZNF597. They further identify novel association in AP4E1, refining the genetic landscape of the known SPPL2A locus. Our results demonstrate that machine learning methods can achieve predictive performance comparable to classical approaches in genetic epidemiology and have the potential to uncover novel loci that remain undetected by traditional GWAS. These insights provide a complementary avenue for advancing the understanding of AD genetics.
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000280043 588__ $$aDataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
000280043 650_7 $$2NLM Chemicals$$aGTPase-Activating Proteins
000280043 650_2 $$2MeSH$$aAlzheimer Disease: genetics
000280043 650_2 $$2MeSH$$aHumans
000280043 650_2 $$2MeSH$$aMachine Learning
000280043 650_2 $$2MeSH$$aGenome-Wide Association Study
000280043 650_2 $$2MeSH$$aGenetic Predisposition to Disease
000280043 650_2 $$2MeSH$$aPolymorphism, Single Nucleotide
000280043 650_2 $$2MeSH$$aAlgorithms
000280043 650_2 $$2MeSH$$aGTPase-Activating Proteins: genetics
000280043 650_2 $$2MeSH$$aNeural Networks, Computer
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