{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Jang SK"],"funding":["NHGRI","National Institute of Mental Health","NIGMS"],"pagination":["101068"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12903449"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["6(2)"],"pubmed_abstract":["Protein language models (PLMs) improve variant effect predictions, but their role in gene discovery for complex traits remains unclear. We introduce an allelic series-based regression test that uses PLM-derived variant effect predictions as proxies for effect sizes, identifying ∼46% more associations than standard burden tests. Extending this to isoform-level analysis, we find 26 gene-trait pairs with stronger associations in non-canonical versus canonical transcripts, highlighting isoform-specific effects. Finally, we identify evolutionary plausible variants (EPVs), missense variants assigned higher likelihoods than the wild-type alleles by PLMs, representing 0.45% of missense variants. EPVs show higher allele frequencies than synonymous variants, consistent with differential selection pr"],"journal":["Cell genomics"],"pubmed_title":["Leveraging protein language models to identify complex trait associations with previously inaccessible classes of functional rare variants."],"pmcid":["PMC12903449"],"funding_grant_id":["R01MH130581"],"pubmed_authors":["Ntranos V","Zaitlen N","Border R","Wei A","Tuan D","Jang SK","Flint J","Sankararaman S","Wang Z","An U"],"additional_accession":[]},"is_claimable":false,"name":"Leveraging protein language models to identify complex trait associations with previously inaccessible classes of functional rare variants.","description":"Protein language models (PLMs) improve variant effect predictions, but their role in gene discovery for complex traits remains unclear. We introduce an allelic series-based regression test that uses PLM-derived variant effect predictions as proxies for effect sizes, identifying ∼46% more associations than standard burden tests. Extending this to isoform-level analysis, we find 26 gene-trait pairs with stronger associations in non-canonical versus canonical transcripts, highlighting isoform-specific effects. Finally, we identify evolutionary plausible variants (EPVs), missense variants assigned higher likelihoods than the wild-type alleles by PLMs, representing 0.45% of missense variants. EPVs show higher allele frequencies than synonymous variants, consistent with differential selection pr","dates":{"release":"2026-01-01T00:00:00Z","publication":"2026 Feb","modification":"2026-07-15T18:02:43.737Z","creation":"2026-07-08T03:08:33.915Z"},"accession":"S-EPMC12903449","cross_references":{"pubmed":["41265447"],"doi":["10.1016/j.xgen.2025.101068"]}}