ReviewNature genetics2025
A standardized framework for circulating blood proteomics.
Review in Nature genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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
11 citing papers in PubMed.
- Towards liquid biopsy-based analysis of antitumour immunity.Nature reviews. Clinical oncology · 2026Review
- From Machine Learning-Enhanced Proteomics to a Validated Diagnostic Model: A Pipeline for Breast Cancer Biomarker Discovery via Independent and Transcriptomic Corroboration.Bioengineering (Basel, Switzerland) · 2026Article
- Population proteomics for equitable precision medicine.EMBO molecular medicine · 2026Article
- Ensuring multiomics data reproducibility for artificial intelligence with reference materials as a common calibrator.Nature biotechnology · 2026Article
- Artificial intelligence needs a common ruler.Innovation (Cambridge (Mass.)) · 2026Article
- Immunoglobulin sub-class levels define inter-donor plasma variability: a longitudinal dual-lab study.Molecular systems biology · 2026Article
- Translational bottlenecks in blood-based proteomics.EMBO molecular medicine · 2026Article
- Transcending genome-wide association studies to create useful multi-omic views of glaucoma.Progress in retinal and eye research · 2026Review
- Systematic Evaluation of Depletion and Enrichment Technologies for Platelet-Free Plasma Proteomics.Journal of proteome research · 2026Article
- Robotic perturbation proteomics and AI agents enable scalable drug mechanism discovery.bioRxiv : the preprint server for biology · 2026Article
- Blood proteomics: insights from public data.Genome biology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The circulating blood proteome holds immense potential for biomarker discovery and understanding disease mechanisms. Notable advances in mass spectrometry and affinity-based technologies have been made, but data integration across studies and platforms is hindered by the absence of unified analytical standards. This limitation impedes comprehensive exploration of human biology across diverse phenotypes and cohorts as well as the translation of findings into clinical applications. The disparities between datasets, stemming from a combination of factors related to differences in sample collection, pre-analytical handling, measurement methods and instrumentation, further complicate data integration. In this Perspective, we outline key challenges in blood-based proteomics and propose actionable strategies. Central to our recommendations are high-quality, technology-agnostic reference samples, which can bridge disparate datasets and enable robust cross-study comparisons. By fostering interconnected investigations across proteomic technologies, blood sample collections, clinical phenotypes and different populations, these references will accelerate the field and its translation.
Indexed as
Identifiers
40987950What OpenQuestion 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 OpenQuestion graph.