Whole blood transcriptomics atlas across human diseases

Abstract We present a WBT Atlas, comprising 4444 WBT samples across 98 distinct health conditions, enabling systematic exploration of disease-associated transcriptomic signatures. Health condition–specific profiles are characterized across immune, metabolic, and cell-type specific features at the gene, gene module, and pathway levels. By integrating matched plasma proteomics data from 1280 participants across 28 health conditions, we further assess blood RNA–protein relationships and demonstrate their complementary biological roles. By integrating RNA and protein signatures, we develop multi-class classification models that accurately distinguish among a wide range of health conditions, with integrated models consistently outperforming those based on single-omics data alone. The identified RNA and protein signatures are validated across ten independent WBT cohorts and the UK Biobank. Together, the WBT Atlas provides a genome-wide resource that enables translational discovery in precision medicine.

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Publication Details

Journal
Nature Communications
Published
2026-10-12
DOI
https://doi.org/10.1038/s41467-026-78440-w
Primary Topic
Bioinformatics and Genomic Networks
Type
article
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article

Whole blood transcriptomics atlas across human diseases

Necip Altundaş, Fatih Alper, Nurhak Aksungur, Büşra AKPINAR et al.
Nature Communications
Bioinformatics and Genomic Networks
article

Whole blood transcriptomics atlas across human diseases

Necip Altundaş, Fatih Alper, Nurhak Aksungur, Büşra AKPINAR, Atilla Çayır, Yahya Gül, Çiğdem Yüce Kahraman, Fatma Kesmez Can, Özlem Kudaş, Hacer Akgül Ceyhun, Emre Green, Esra Laloğlu, Esra Dişçi, Handan Alay, Rıfat Peksöz, Fatma Şimşek, Serap Sarı, Abdülgani Tatar, Ebru Simsek, Buğra Kerget, Ayşe Sena Donmez, Bahadır Utlu, Fuat Laloğlu, Emine Çinici, Ayşenur Dostbil, Zülal Özkurt, Naci Cevi̇z, Esat Fahri Aydın, Ömer Araz, Ömer Erkan Yapça, Erdal Tekin, Ali Bilal Ulaş, Hakan Döneray, Emsal Pınar Topdağı Yılmaz, Pınar Tosun Taşar, Mustafa Ceylan, Taner Arabacı, Mürsel Karadavut, Yavuz Albayrak, Gürkan Öztürk, Momen Kanjee, Derya Cevizli, Can Sevinç, Gamze Nur Cimilli Şenocak, Murat Kartal, Sinan Yılar, Atilla Eroğlu, Eyüp Şenocak, Arzu Onder Tatar, Mehmet İlhan YILDIRGAN, B. Erkut, Sultan Tuna Akgöl GÜR, Kenan Çadırcı, Mehmet Cenk Turğut, Kemalettin Özden, Fatma Tortum, María Bueno Álvez, Halil Özcan, Ahmet Emre Paksoy, Hilal Kızıltunç Özmen, Mengzhen Li, Güngör Akçay, Mehmet Akif Şirin, Muhammed Hakan Tas, Mirze Muhammet Özen, Serap Kılıç Kaya, Nuray Bilge, Büşra Saruhan, Yakup Kumtepe, Yunus Emre Aktaş, Turgut Yapanoglu, Sumeyye Ozturk Eren, Nazim Dogan, Mevlana Gul, Ali Gur, Ayse Albayrak, Bulent Albayrak, Ozkan Cinici, Tugba Koca Lacin, Sabri Selcuk Atamanalp, Salih Kara, Mustafa Kara, Yunus Emre Topdagi, Muhammed Akif Guler, Mufide Akcay, Gulden Sincan, Serdar Saritas, Ertugrul Karatas, Yener Aydın, Erdem Karadeniz, Ibrahim Kocer, Ozgur Ozmen, Husnu Kursat, Eyup Serhat Calik, Ayse Ozden, Merve Ulku, Hasan Abbas Guliyev, Esra Tanriverdi, Ugur Kaya
article en

Abstract

Abstract We present a WBT Atlas, comprising 4444 WBT samples across 98 distinct health conditions, enabling systematic exploration of disease-associated transcriptomic signatures. Health condition–specific profiles are characterized across immune, metabolic, and cell-type specific features at the gene, gene module, and pathway levels. By integrating matched plasma proteomics data from 1280 participants across 28 health conditions, we further assess blood RNA–protein relationships and demonstrate their complementary biological roles. By integrating RNA and protein signatures, we develop multi-class classification models that accurately distinguish among a wide range of health conditions, with integrated models consistently outperforming those based on single-omics data alone. The identified RNA and protein signatures are validated across ten independent WBT cohorts and the UK Biobank. Together, the WBT Atlas provides a genome-wide resource that enables translational discovery in precision medicine.

Nature Communications
Openalex Percentile: Top 23%
Bioinformatics and Genomic Networks
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