Faculty, Staff and Student Publications

Language

English

Publication Date

1-22-2026

Journal

Nature Communications

DOI

10.1038/s41467-025-67814-1

PMID

41571639

PMCID

PMC12847899

PubMedCentral® Posted Date

1-22-2026

PubMedCentral® Full Text Version

Post-print

Abstract

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 ancestry. Furthermore, adjustment for protein-altering variants with opposite directions of effect by platform improves inter-platform protein measure correlation and results in more concordant genetic and phenotypic associations. Hence, protein-altering variants need to be accounted for across ancestries to facilitate platform-concordant and accurate protein measurement.

Keywords

Humans, Proteomics, Antibodies, Genetic Variation, Proteins, Aptamers, Nucleotide, Polymorphism, Single Nucleotide

Published Open-Access

yes

Download

Included in

Public Health Commons

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.