Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes

P Martijn Kolijn; Karl Smith-Byrne; Vernon Burk; Vivian Viallon; Matthew A Lee; Keren Papier; Ziqiao Wang; Anton W Langerak; Florentin Späth; Arjan Diepstra; Christina M Lill; Raul Zamora-Ros; Alessandra Macciotta; Amaia Aizpurua; Rosario Tumino; Nilanjan Chatterjee; Ruth C Travis; Marc J Gunter; Elizabeth A Platz; Elio Riboli; James McKay; Roel C H Vermeulen

doi:10.1038/s41467-025-64534-4

Multi-cohort high-dimensional proteomics reveals early risk markers for lymphoid cancer subtypes

Nat Commun. 2025 Oct 28;16(1):9517. doi: 10.1038/s41467-025-64534-4.

Authors

P Martijn Kolijn^{1

2

3}, Karl Smith-Byrne⁴, Vernon Burk⁵, Vivian Viallon⁶, Matthew A Lee^{6

7}, Keren Papier⁴, Ziqiao Wang⁸, Anton W Langerak³, Florentin Späth⁹, Arjan Diepstra¹⁰, Christina M Lill^{11

12}, Raul Zamora-Ros¹³, Alessandra Macciotta¹⁴, Amaia Aizpurua^{15

16}, Rosario Tumino¹⁷, Nilanjan Chatterjee⁸, Ruth C Travis⁴, Marc J Gunter^{6

18}, Elizabeth A Platz⁵, Elio Riboli¹⁸, James McKay⁶, Roel C H Vermeulen^{19

20}

Affiliations

¹ Division of Environmental Epidemiology and Veterinary Public Health, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands.
² Julius Global Health, the Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands.
³ Department of Immunology, Erasmus MC, Rotterdam, the Netherlands.
⁴ Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
⁵ Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
⁶ International Agency for Research on Cancer (IARC) - World Health Organization, Lyon, France.
⁷ Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
⁸ Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
⁹ Department of Diagnostics and Intervention, Umeå University, Umeå, Sweden.
¹⁰ Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.
¹¹ Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany.
¹² Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, UK.
¹³ Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain.
¹⁴ Centre for Biostatistics, Epidemiology and Public Health (C-BEPH), Department of Clinical and Biological Sciences, University of Turin, Orbassano, Italy.
¹⁵ Sub-Directorate for Public Health and Addictions of Gipuzkoa, Donostia, Spain.
¹⁶ Biodonostia Health Research Institute, Epidemiology of Chronic and Communicable Diseases Group, San Sebastián, Spain.
¹⁷ Hyblean Association for Epidemiology Research, AIRE-ONLUS, Ragusa, Italy.
¹⁸ Cancer Epidemiology and Prevention Research Unit, School of Public Health, Imperial College London, London, UK.
¹⁹ Division of Environmental Epidemiology and Veterinary Public Health, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands. r.c.h.vermeulen@uu.nl.
²⁰ Julius Global Health, the Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, The Netherlands. r.c.h.vermeulen@uu.nl.

Abstract

This study aims to investigate the early stages of lymphoid malignancy pathogenesis and identify pre-diagnostic proteomic markers for lymphoma. Using the SomaScan-7K platform, we analyze 6412 unique plasma proteins in a case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, comprising 4565 participants (484 incident lymphoid malignancy cases, median follow-up 9 years). We identify over 500 unique protein-lymphoid malignancy associations. Enriched pathways include viral protein interactions, cytokine signaling, B-cell receptor signaling, and NF-κB activation, reflecting key mechanisms in lymphoma pathogenesis. Cross-cohort validation of the top 20 FDR-significant proteins reveals concordant nominal significance for 70%-95% of the associations in the UK Biobank (Olink) and ARIC (SomaScan) studies. Time-stratified analyses reveals that a subset of these protein-lymphoma associations is evident over a decade before diagnosis. These findings highlight the potential of circulating proteomic markers in risk stratification, early diagnosis, and targeted prevention strategies for lymphoid malignancies.

MeSH terms

Aged
Biomarkers, Tumor* / blood
Biomarkers, Tumor* / metabolism
Blood Proteins / metabolism
Cohort Studies
Female
Humans
Lymphoma* / blood
Lymphoma* / diagnosis
Lymphoma* / metabolism
Male
Middle Aged
Prospective Studies
Proteomics* / methods
Risk Factors

Substances

Biomarkers, Tumor
Blood Proteins

Abstract

MeSH terms

Substances

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