ArticleDiabetes2026
Longitudinal Repeated Protein Measurements in a Multiethnic Cohort Identify Novel Diabetes Biomarkers That Reveal Unique Disease Pathways.
Article in Diabetes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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21 authors.
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Abstract
Circulating diabetes biomarkers have been identified with proteomics measured at a single time point, but what is additionally provided by longitudinal repeated measurements in the same individuals, over many years, is unknown. We studied participants in the Multi-Ethnic Study of Atherosclerosis (MESA; n = 5,322; mean baseline age, 61.7 years) at exams 1 (2000-2002), 5 (2010-2012), and 6 (2016-2018) profiled with the Olink Explore (3 K) platform. Associations with incident diabetes, mostly of type 2, were modeled using Cox proportional hazards with exam 1 proteins (i.e., single time point) and time-updating Cox with proteins from all three exams (i.e., longitudinal repeated) adjusted for clinical risk factors. We identified 27 novel single time point associations and up to a fourfold increase in longitudinal associations (false discovery rate < 0.05), with a proportional increase in the number consistent with causality via cis-Mendelian randomization (∼5%) and a smaller overlap in MESA longitudinal versus single associations with UK Biobank single time point findings (42% vs. 87%, respectively). Compared with small-molecule metabolism pathway enrichment among the shared proteins, proteins unique to the longitudinal analyses enriched for protein and cellular processing pathways. We conclude that longitudinal repeated measurements identify a number of distinct disease biomarkers, in part by revealing the progression of relevant biological processes within an individual closer to a clinical diabetes diagnosis versus single measurements. ARTICLE HIGHLIGHTS: There is up to a fourfold increase in diabetes biomarkers identified with longitudinal repeated versus single time point proteomic measurements. The increase in biomarkers identified with longitudinal repeated measurements is supported by a similar proportion being nominated as causal for type 2 diabetes with Mendelian randomization. Proteins unique to the longitudinal repeated analyses highlighted biological pathways (e.g., posttranslational protein modification and cellular structure and cycle regulation) that were distinct from pathways enriched among the shared proteins (e.g., small-molecule metabolic and catabolic processes). Longitudinal protein measurements identify additional novel disease biomarkers and disparate biological pathways compared with single measurement analyses.
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