A human pan-disease blood atlas of the circulating proteome
Álvez, M.B. ; Reepalu, A. LU
and Uhlén, M.
(2025)
In Science
390(6779).
- Abstract
- The human blood proteome provides a holistic readout of health states through the assessment of thousands of circulating proteins. In this study, we present a pan-disease resource to enable the study of diverse disease phenotypes within a harmonized proteomics dataset. by profiling protein concentrations across 59 diseases and healthy cohorts, we identified proteins associated with age, sex, and body mass index, as well as disease-specific signatures. This study highlights shared and distinct protein patterns across conditions, demonstrating the power of a unified proteomics approach to uncover biological insights. The dataset, covering 8262 individuals and up to 5416 proteins, serves as an online resource for exploring disease-specific... (More)
- The human blood proteome provides a holistic readout of health states through the assessment of thousands of circulating proteins. In this study, we present a pan-disease resource to enable the study of diverse disease phenotypes within a harmonized proteomics dataset. by profiling protein concentrations across 59 diseases and healthy cohorts, we identified proteins associated with age, sex, and body mass index, as well as disease-specific signatures. This study highlights shared and distinct protein patterns across conditions, demonstrating the power of a unified proteomics approach to uncover biological insights. The dataset, covering 8262 individuals and up to 5416 proteins, serves as an online resource for exploring disease-specific protein profiles and advancing precision medicine research. © 2025 American Association for the Advancement of Science. All rights reserved. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/bbeb4225-aa90-4466-871b-cba5b1a13e88
- author
- Álvez, M.B.
; Reepalu, A.
LU
and Uhlén, M.
- author collaboration
- organization
- publishing date
- 2025
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Adult, Age Factors, Blood Proteins, Body Mass Index, Disease, Female, Humans, Male, Middle Aged, Precision Medicine, Proteome, Proteomics, Sex Factors, carboxylesterase, CD33 antigen, ectodysplasin A, epididymal secretory protein, fibroblast growth factor 1, fibroblast growth factor 21, glutathione transferase A3, leptin, placenta protein 14, protein kinase C, proteome, serine proteinase inhibitor, protein blood level, blood system disorder, body mass, medicine, precision, protein, proteomics, adult, aged, allergy, angiogenesis, area under the curve, Article, asthma, autoimmune disease, bioinformatics, blood level, cardiometabolic risk, cardiovascular disease, cell survival, childhood disease, clinical significance, controlled study, correlation analysis, data base, DNA probe, electronic health record, female, fertilization, gene expression, gene ontology, high throughput sequencing, human, immunocompetent cell, inflammation, limit of detection, liquid chromatography-mass spectrometry, liver cancer, logistic regression analysis, longitudinal study, machine learning, male, male genital system, mass spectrometry, metabolic disorder, metabolic fatty liver, metabolomics, multiomics, obesity, oocyte development, pan disease blood atlas, phenotype, polymerase chain reaction, predictive model, protein expression, protein fingerprinting, puberty, rheumatoid arthritis, systemic lupus erythematosus, transcriptomics, whole genome sequencing, age, diseases, middle aged, personalized medicine, sex factor
- in
- Science
- volume
- 390
- issue
- 6779
- publisher
- American Association for the Advancement of Science (AAAS)
- external identifiers
-
- scopus:105025246161
- ISSN
- 0036-8075
- DOI
- 10.1126/science.adx2678
- language
- English
- LU publication?
- yes
- id
- bbeb4225-aa90-4466-871b-cba5b1a13e88
- date added to LUP
- 2026-04-01 09:47:20
- date last changed
- 2026-04-01 09:48:13
@article{bbeb4225-aa90-4466-871b-cba5b1a13e88,
abstract = {{The human blood proteome provides a holistic readout of health states through the assessment of thousands of circulating proteins. In this study, we present a pan-disease resource to enable the study of diverse disease phenotypes within a harmonized proteomics dataset. by profiling protein concentrations across 59 diseases and healthy cohorts, we identified proteins associated with age, sex, and body mass index, as well as disease-specific signatures. This study highlights shared and distinct protein patterns across conditions, demonstrating the power of a unified proteomics approach to uncover biological insights. The dataset, covering 8262 individuals and up to 5416 proteins, serves as an online resource for exploring disease-specific protein profiles and advancing precision medicine research. © 2025 American Association for the Advancement of Science. All rights reserved.}},
author = {{Álvez, M.B. and Reepalu, A. and Uhlén, M.}},
issn = {{0036-8075}},
keywords = {{Adult; Age Factors; Blood Proteins; Body Mass Index; Disease; Female; Humans; Male; Middle Aged; Precision Medicine; Proteome; Proteomics; Sex Factors; carboxylesterase; CD33 antigen; ectodysplasin A; epididymal secretory protein; fibroblast growth factor 1; fibroblast growth factor 21; glutathione transferase A3; leptin; placenta protein 14; protein kinase C; proteome; serine proteinase inhibitor; protein blood level; blood system disorder; body mass; medicine; precision; protein; proteomics; adult; aged; allergy; angiogenesis; area under the curve; Article; asthma; autoimmune disease; bioinformatics; blood level; cardiometabolic risk; cardiovascular disease; cell survival; childhood disease; clinical significance; controlled study; correlation analysis; data base; DNA probe; electronic health record; female; fertilization; gene expression; gene ontology; high throughput sequencing; human; immunocompetent cell; inflammation; limit of detection; liquid chromatography-mass spectrometry; liver cancer; logistic regression analysis; longitudinal study; machine learning; male; male genital system; mass spectrometry; metabolic disorder; metabolic fatty liver; metabolomics; multiomics; obesity; oocyte development; pan disease blood atlas; phenotype; polymerase chain reaction; predictive model; protein expression; protein fingerprinting; puberty; rheumatoid arthritis; systemic lupus erythematosus; transcriptomics; whole genome sequencing; age; diseases; middle aged; personalized medicine; sex factor}},
language = {{eng}},
number = {{6779}},
publisher = {{American Association for the Advancement of Science (AAAS)}},
series = {{Science}},
title = {{A human pan-disease blood atlas of the circulating proteome}},
url = {{http://dx.doi.org/10.1126/science.adx2678}},
doi = {{10.1126/science.adx2678}},
volume = {{390}},
year = {{2025}},
}