ArticleResearch square2026
A Circulating Proteomic Signature of Allostatic Load Predicts Multisystem Disease and Mortality.
Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Beyond disclosure: setting standards for AI use in publishing in the journal Pediatric Research.Pediatric research · 2026Article
Corrections and comments
- Updated by
Authors and funding
11 authors.
Funding
Abstract
Chronic stress contributes to the development of cardiometabolic, malignant, and other chronic diseases through cumulative multisystem physiological dysregulation, conceptualized as allostatic load (AL). However, traditional AL relies on heterogeneous clinical biomarkers that limit reproducibility and translational utility. Here, we develop and validate ProAL50, a proteomics-based measure of AL derived from 50 circulating proteins. Using high-dimensional plasma proteomic data from the UK Biobank, we constructed ProAL50 via penalized regression and stability selection and externally validated it in the Coronary Artery Risk Development in Young Adults (CARDIA) Study. ProAL50 closely mirrored traditional AL in its associations with sociodemographic characteristics, lifestyle behaviors, physical and mental health, inflammation, and biological aging, supporting strong construct validity. Beyond replication, ProAL50 consistently demonstrated stronger associations with incident chronic diseases, including all cancers, type 2 diabetes, ischemic heart disease, chronic lung disease, and chronic kidney disease, and with all-cause and cause-specific mortality. Functional enrichment analyses revealed that ProAL50 proteins cluster within lipid metabolic and immune-inflammatory pathways. These findings establish ProAL50 as a scalable, biologically grounded measure of cumulative stress that not only replaces traditional AL but surpasses it in predicting disease risk and mortality, offering a novel tool for population health and translational research.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.