Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom
Andrew Wong
MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom
Richard J Silverwood
Centre for Longitudinal Studies, University College London, London, United Kingdom
Anika Knuppel
MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom
Dylan M Williams
MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
Department of Epidemiology and Public Health, University College London, London, United Kingdom
Srinivasa Vittal Katikireddi
MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, United Kingdom
George B Ploubidis
Centre for Longitudinal Studies, University College London, London, United Kingdom
Ellen J Thompson
Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom; MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom
Ruth CE Bowyer
Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; AI for Science and Government, The Alan Turing Institute, London, United Kingdom
Xinyuan Zhang
Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom
Golboo Abbasian
Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom
Maria Paz Garcia
Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom
Deborah Hart
Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom
Jeffrey Seow
Department of Infectious Diseases, King's College London, London, United Kingdom
Carl Graham
Department of Infectious Diseases, King's College London, London, United Kingdom
Neophytos Kouphou
Department of Infectious Diseases, King's College London, London, United Kingdom
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
Sarah Matthews
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
Thomas Breeze
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
Michael Crawford
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
Lynn Molloy
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
Alex SF Kwong
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom; Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
Katie Doores
Department of Infectious Diseases, King's College London, London, United Kingdom
Nishi Chaturvedi
MRC Unit for Lifelong Health and Ageing, University College London, London, United Kingdom
Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom; Guy’s & St Thomas’s NHS Foundation Trust, London, United Kingdom
Nicholas J Timpson
Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
Department of Twin Research and Genetic Epidemiology, King’s College London, London, United Kingdom; Guy’s & St Thomas’s NHS Foundation Trust, London, United Kingdom
Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody levels can be used to assess humoral immune responses following SARS-CoV-2 infection or vaccination, and may predict risk of future infection. Higher levels of SARS-CoV-2 anti-Spike antibodies are known to be associated with increased protection against future SARS-CoV-2 infection. However, variation in antibody levels and risk factors for lower antibody levels following each round of SARS-CoV-2 vaccination have not been explored across a wide range of socio-demographic, SARS-CoV-2 infection and vaccination, and health factors within population-based cohorts. Methods: Samples were collected from 9361 individuals from TwinsUK and ALSPAC UK population-based longitudinal studies and tested for SARS-CoV-2 antibodies. Cross-sectional sampling was undertaken jointly in April-May 2021 (TwinsUK, N=4256; ALSPAC, N=4622), and in TwinsUK only in November 2021-January 2022 (N=3575). Variation in antibody levels after first, second, and third SARS-CoV-2 vaccination with health, socio-demographic, SARS-CoV-2 infection, and SARS-CoV-2 vaccination variables were analysed. Using multivariable logistic regression models, we tested associations between antibody levels following vaccination and: (1) SARS-CoV-2 infection following vaccination(s); (2) health, socio-demographic, SARS-CoV-2 infection, and SARS-CoV-2 vaccination variables. Results: Within TwinsUK, single-vaccinated individuals with the lowest 20% of anti-Spike antibody levels at initial testing had threefold greater odds of SARS-CoV-2 infection over the next 6–9 months (OR = 2.9, 95% CI: 1.4, 6.0), compared to the top 20%. In TwinsUK and ALSPAC, individuals identified as at increased risk of COVID-19 complication through the UK ‘Shielded Patient List’ had consistently greater odds (two- to fourfold) of having antibody levels in the lowest 10%. Third vaccination increased absolute antibody levels for almost all individuals, and reduced relative disparities compared with earlier vaccinations. Conclusions: These findings quantify the association between antibody level and risk of subsequent infection, and support a policy of triple vaccination for the generation of protective antibodies. Funding: Antibody testing was funded by UK Health Security Agency. The National Core Studies program is funded by COVID-19 Longitudinal Health and Wellbeing – National Core Study (LHW-NCS) HMT/UKRI/MRC ([MC_PC_20030] and [MC_PC_20059]). Related funding was also provided by the NIHR 606 (CONVALESCENCE grant [COV-LT-0009]). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. The UK Medical Research Council and Wellcome (Grant ref: [217065/Z/19/Z]) and the University of Bristol provide core support for ALSPAC.