Evidence map›Paper›PMID 42410022›Full record

ReviewNature protocols2026

A scalable high-throughput serolomics platform for profiling serum antibody responses in large-scale population-based cohorts.

Lea Kröller, Rima Jeske, Birgitta Michels, Julia Butt, Iona Millwood, Christiana Kartsonaki, Zhengming Chen, Jun Lv, Liming Li, Rasmus Gustafsson and 8 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Lea KröllerDivision of Infections and Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany. l.kroeller@dkfz-heidelberg.de.ORCID http://orcid.org/0009-0008-9365-0796
Rima JeskeDivision of Infections and Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
Birgitta MichelsDivision of Infections and Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.ORCID http://orcid.org/0000-0001-9948-4567
Julia ButtDivision of Infections and Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.
Iona MillwoodClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Christiana KartsonakiClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Zhengming ChenClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China.ORCID http://orcid.org/0000-0001-7916-3870
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China.
Rasmus GustafssonCenter for Molecular Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Andrew GordonClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Frederik RomerClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Hannah FryClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Sarah ClarkClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Michael HillClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-3861-6105
Ling YangClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0001-5750-6588
Alexander MentzerThe Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-4502-2209
Tim WaterboerDivision of Infections and Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany.

Funding

Cancer Research UK (CRUK) C16077/A29186
6 · The paper itself

Abstract

Seroepidemiological assays play a crucial role in tracking immunity and infectious disease exposure across populations. Here we describe an automated assay platform that robustly quantifies antibodies against up to 100 antigens in a single reaction, using Luminex suspension array technology, alongside generating ample quality control measures. This automated multiplex serology workflow is an advancement of our previously developed manual and hybrid multiplex serology platforms. It combines multiple liquid handling systems (Biomeki7, BioTek 405 LS) and bead separation technology (KingFisher Flex) to improve scalability and reproducibility and facilitate its application in large-scale population-based cohorts. Study samples undergo automated processing, and antibody levels are quantified using the Luminex Flexmap3D instrument. A custom R-based application monitors process parameters and visualizes readouts in real time. Daily quality control samples allow subsequent normalization over extended periods of time and across reagent batches. Compared with previous assay versions, the higher degree of automation requires fewer laboratory operators and results in improved robustness and a more continuous throughput. Assay robustness is excellent, with median coefficients of variations between 2.8% and 11.7%, with no relevant batch effects over a 6-month period. Reproducibility across 47 antigens and 91 duplicate samples is remarkably high (R

Identifiers

PMID42410022

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.