ReviewImmunology2018
Prospects from systems serology research.
Review in Immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 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
48 citing papers in PubMed, 75 citations in OpenAlex.
- Neutralizing antibody immune correlates in COVAIL trial recipients of an mRNA second COVID-19 vaccine boost.Nature communications · 2025Trial
- A systems approach to elucidate personalized mechanistic complexities of antibody-Fc receptor activation post-vaccination.Cell reports. Medicine · 2021Trial
- Human Antibody Isotypes, Subclasses, Allotypes and Fc Biology: Clinical Implications in Infectious Diseases, Autoimmunity, and Cancer.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Malaria serology for surveillance, insights into immunity, and vaccine development.Infection and immunity · 2026Review
- Systems serology identifies FcR-related autoantibody signatures and functions for Sjögren's syndrome.EMBO molecular medicine · 2026Article
- Fc effector functions in RNA viral infections: mechanisms of antiviral immunity and implications for vaccine design.Frontiers in immunology · 2026Review
- Increased SARS-CoV-2 IgG4 has variable consequences dependent upon Fc function, Fc receptor polymorphism, and viral variant.Science advances · 2025Article
- Dissecting the properties of circulating IgG against streptococcal pathogens through a combined systems antigenomics-serology workflow.Nature communications · 2025Article
- A multivalent binding model infers antibody Fc species from systems serology.PLoS computational biology · 2024Article
- A systems serology approach to identifying key antibody correlates of protection from cerebral malaria in Malawian children.BMC medicine · 2024Article
- Dissecting humoral immune responses to an MVA-vectored MERS-CoV vaccine in humans using a systems serology approach.iScience · 2024Article
- Protective mechanisms of nonneutralizing antiviral antibodies.PLoS pathogens · 2023Review
- Antibody Fc-binding profiles and ACE2 affinity to SARS-CoV-2 RBD variants.Medical microbiology and immunology · 2023Article
- Predicting Vibrio cholerae infection and symptomatic disease: a systems serology study.The Lancet. Microbe · 2023Article
- Correlates of immunity to Group A Streptococcus: a pathway to vaccine development.NPJ vaccines · 2023Review
- A systems serology approach to the investigation of infection-induced antibody responses and protection in trachoma.Frontiers in immunology · 2023Article
- Functional assays to evaluate antibody-mediated responses againstFrontiers in cellular and infection microbiology · 2023Review
- Distinct anti-NP, anti-RBD and anti-Spike antibody profiles discriminate death from survival in COVID-19.Frontiers in immunology · 2023Article
- Polyfunctional antibodies: a path towards precision vaccines for vulnerable populations.Frontiers in immunology · 2023Review
- Persistence of MERS-CoV-spike-specific B cells and antibodies after late third immunization with the MVA-MERS-S vaccine.Cell reports. Medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antibodies are highly functional glycoproteins capable of providing immune protection through multiple mechanisms, including direct pathogen neutralization and the engagement of their Fc portions with surrounding effector immune cells that induce anti-pathogenic responses. Small modifications to multiple antibody biophysical features induced by vaccines can significantly alter functional immune outcomes, though it is difficult to predict which combinations confer protective immunity. In order to give insight into the highly complex and dynamic processes that drive an effective humoral immune response, here we discuss recent applications of 'Systems Serology', a new approach that uses data-driven (also called 'machine learning') computational analysis and high-throughput experimental data to infer networks of important antibody features associated with protective humoral immunity and/or Fc functional activity. This approach offers the ability to understand humoral immunity beyond single correlates of protection, assessing the relative importance of multiple biophysical modifications to antibody features with multivariate computational approaches. Systems Serology has the exciting potential to help identify novel correlates of protection from infection and may generate a more comprehensive understanding of the mechanisms behind protection, including key relationships between specific Fc functions and antibody biophysical features (e.g. antigen recognition, isotype, subclass and/or glycosylation events). Reviewed here are some of the experimental and computational technologies available for Systems Serology research and evidence that the application has broad relevance to multiple different infectious diseases including viruses, bacteria, fungi and parasites.
Indexed as
Identifiers
What 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.