biostudies-literatureNicholas JCNCATS NIH HHSU.S. Department of Health & Human Services | NIH | National Institute of General Medical SciencesNIA NIH HHSNCRR NIH HHSU.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS)NHLBI NIH HHSU.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood InstituteU.S. Department of Health & Human Services | National Institutes of Health (NIH)NIDDK NIH HHSNHGRI NIH HHSU.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI)NIH HHSU.S. Department of Health & Human Services | National Institutes of HealthNIGMS NIH HHS1054https://www.ebi.ac.uk/biostudies/studies/S-EPMC12847899biostudies-literatureUnknown17(1)Measures from affinity-proteomics platforms often correlate poorly, challenging interpretation of protein associations with genetic variants and phenotypes. Here, we examine 2157 proteins measured on both SomaScan 7k and Olink Explore 3072 across 1930 participants with genetic similarity to European, African, East Asian, and Admixed American ancestry references. Inter-platform correlation coefficients for these 2157 proteins follow a bimodal distribution (median r = 0.30). We evaluate protein measure associations with genetic variants, and find approximately 25-30% of the signals on each platform are likely driven by protein-altering variants. We highlight 80 proteins that correlate differently across ancestry groups likely in part due to differing protein-altering variant frequencies by aNature communicationsCross-ancestry comparison of aptamer and antibody protein measures.PMC128478991F31HL176194-01A1UL1 TR001881R01 HL071205N01 HC095166N01 HC095165N01 HC095168N01 HC095167N01 HC095169N01 HC095160R01 HL159081N01 HC095162N01 HC095161N01 HC095164F31 HL176194N01 HC095163U01 AG082042UL1 TR000040R01 HL071259R01HL133870R01 HL071258U54 HG003067R01 HL120393R01 HL071051R01 HL071251R01 HL071250UM1 DK078616P30 DK063491R01 DK072193UL1 TR001420R01 HL133870R01 HL117626UL1 RR033176T32 GM135128R01DK07219375N98025D0002275N92020D0000775N98025D0002575N98025D0002475N98025D0002775N98025D0002675N98025D0002875N92020D0000175N92020D0000275N92020D0000575N92020D0000675N92020D00003T32GM13512875N92020D00004HHSN268201500003CUL1 TR001079N01 HC095159R01 HL151855R01 HL146860R01 HL105756HHSN268201500003IEkunwe LPsaty BMGerszten RERotter JIGill DGuo XYoung KLDurda PManning ARich SSRuan PDoyle MFDubin RWilson JGWen JBowler RPSun QMychaleckyj JCTracy RPBroadaway KABlackwell TFloyd JSChen JRaffield LMWood ACLi YManichaikul ALange LAKatz DHNicholas JCGanz PMeigs JBRooney MRClish CBCornell EDeo RDebban CLShah AMPratte KAJohnson CTahir UAAguet FCruz DESevilla-Gonzalez MHoogeveen RCTaylor KDReiner APOlson NCCoresh JYu BMohlke KLMi MYfalseCross-ancestry comparison of aptamer and antibody protein measures.Measures from affinity-proteomics platforms often correlate poorly, challenging interpretation of protein associations with genetic variants and phenotypes. Here, we examine 2157 proteins measured on both SomaScan 7k and Olink Explore 3072 across 1930 participants with genetic similarity to European, African, East Asian, and Admixed American ancestry references. Inter-platform correlation coefficients for these 2157 proteins follow a bimodal distribution (median r = 0.30). We evaluate protein measure associations with genetic variants, and find approximately 25-30% of the signals on each platform are likely driven by protein-altering variants. We highlight 80 proteins that correlate differently across ancestry groups likely in part due to differing protein-altering variant frequencies by a2026-01-01T00:00:00Z2026 Jan2026-06-13T06:23:01.848Z2026-06-13T03:12:09.581ZS-EPMC128478994157163910.1038/s41467-025-67814-1