Long term intrinsic cycling in human life course antibody responses to influenza A(H3N2): an observational and modeling study.
antibody
dynamics
epidemiology
global health
influenza
viruses
Journal
eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614
Informations de publication
Date de publication:
02 12 2022
02 12 2022
Historique:
received:
28
06
2022
accepted:
01
12
2022
pubmed:
3
12
2022
medline:
21
12
2022
entrez:
2
12
2022
Statut:
epublish
Résumé
Over a life course, human adaptive immunity to antigenically mutable pathogens exhibits competitive and facilitative interactions. We hypothesize that such interactions may lead to cyclic dynamics in immune responses over a lifetime. To investigate the cyclic behavior, we analyzed hemagglutination inhibition titers against 21 historical influenza A(H3N2) strains spanning 47 years from a cohort in Guangzhou, China, and applied Fourier spectrum analysis. To investigate possible biological mechanisms, we simulated individual antibody profiles encompassing known feedbacks and interactions due to generally recognized immunological mechanisms. We demonstrated a long-term periodicity (about 24 years) in individual antibody responses. The reported cycles were robust to analytic and sampling approaches. Simulations suggested that individual-level cross-reaction between antigenically similar strains likely explains the reported cycle. We showed that the reported cycles are predictable at both individual and birth cohort level and that cohorts show a diversity of phases of these cycles. Phase of cycle was associated with the risk of seroconversion to circulating strains, after accounting for age and pre-existing titers of the circulating strains. Our findings reveal the existence of long-term periodicities in individual antibody responses to A(H3N2). We hypothesize that these cycles are driven by preexisting antibody responses blunting responses to antigenically similar pathogens (by preventing infection and/or robust antibody responses upon infection), leading to reductions in antigen-specific responses over time until individual's increasing risk leads to an infection with an antigenically distant enough virus to generate a robust immune response. These findings could help disentangle cohort effects from individual-level exposure histories, improve our understanding of observed heterogeneous antibody responses to immunizations, and inform targeted vaccine strategy. This study was supported by grants from the NIH R56AG048075 (DATC, JL), NIH R01AI114703 (DATC, BY), the Wellcome Trust 200861/Z/16/Z (SR), and 200187/Z/15/Z (SR). This work was also supported by research grants from Guangdong Government HZQB-KCZYZ-2021014 and 2019B121205009 (YG and HZ). DATC, JMR and SR acknowledge support from the National Institutes of Health Fogarty Institute (R01TW0008246). JMR acknowledges support from the Medical Research Council (MR/S004793/1) and the Engineering and Physical Sciences Research Council (EP/N014499/1). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Sections du résumé
Background
Over a life course, human adaptive immunity to antigenically mutable pathogens exhibits competitive and facilitative interactions. We hypothesize that such interactions may lead to cyclic dynamics in immune responses over a lifetime.
Methods
To investigate the cyclic behavior, we analyzed hemagglutination inhibition titers against 21 historical influenza A(H3N2) strains spanning 47 years from a cohort in Guangzhou, China, and applied Fourier spectrum analysis. To investigate possible biological mechanisms, we simulated individual antibody profiles encompassing known feedbacks and interactions due to generally recognized immunological mechanisms.
Results
We demonstrated a long-term periodicity (about 24 years) in individual antibody responses. The reported cycles were robust to analytic and sampling approaches. Simulations suggested that individual-level cross-reaction between antigenically similar strains likely explains the reported cycle. We showed that the reported cycles are predictable at both individual and birth cohort level and that cohorts show a diversity of phases of these cycles. Phase of cycle was associated with the risk of seroconversion to circulating strains, after accounting for age and pre-existing titers of the circulating strains.
Conclusions
Our findings reveal the existence of long-term periodicities in individual antibody responses to A(H3N2). We hypothesize that these cycles are driven by preexisting antibody responses blunting responses to antigenically similar pathogens (by preventing infection and/or robust antibody responses upon infection), leading to reductions in antigen-specific responses over time until individual's increasing risk leads to an infection with an antigenically distant enough virus to generate a robust immune response. These findings could help disentangle cohort effects from individual-level exposure histories, improve our understanding of observed heterogeneous antibody responses to immunizations, and inform targeted vaccine strategy.
Funding
This study was supported by grants from the NIH R56AG048075 (DATC, JL), NIH R01AI114703 (DATC, BY), the Wellcome Trust 200861/Z/16/Z (SR), and 200187/Z/15/Z (SR). This work was also supported by research grants from Guangdong Government HZQB-KCZYZ-2021014 and 2019B121205009 (YG and HZ). DATC, JMR and SR acknowledge support from the National Institutes of Health Fogarty Institute (R01TW0008246). JMR acknowledges support from the Medical Research Council (MR/S004793/1) and the Engineering and Physical Sciences Research Council (EP/N014499/1). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Identifiants
pubmed: 36458815
doi: 10.7554/eLife.81457
pii: 81457
pmc: PMC9757834
doi:
pii:
Substances chimiques
Influenza Vaccines
0
Antibodies, Viral
0
Types de publication
Observational Study
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Medical Research Council
ID : MR/S004793/1
Pays : United Kingdom
Organisme : NIAID NIH HHS
ID : R01 AI114703
Pays : United States
Organisme : FIC NIH HHS
ID : R01 TW008246
Pays : United States
Organisme : Medical Research Council
ID : MR/J008761/1
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 200187/Z/15/Z
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom
Organisme : NIA NIH HHS
ID : R56 AG048075
Pays : United States
Organisme : Wellcome Trust
ID : 200861/Z/16/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_19012
Pays : United Kingdom
Informations de copyright
© 2022, Yang et al.
Déclaration de conflit d'intérêts
BY, JR, HZ, CM, JH, KK, RS, CJ, YG No competing interests declared, BG BGC received financial research support through his institution from Merck for unrelated work, JL JL receives research support from CDC and NIH-NIGMS for for unrelated work, SR SR receives grants from Wellcome Trust, DC DATC received financial research support through his institution from Merck for unrelated work
Références
Mol Ther. 2001 Mar;3(3):395-402
pubmed: 11273782
Nature. 2003 Jul 17;424(6946):303-6
pubmed: 12867979
Am J Epidemiol. 2012 May 15;175(10):1062-74
pubmed: 22411862
Nat Commun. 2011 Aug 09;2:423
pubmed: 21829185
N Engl J Med. 2007 Nov 8;357(19):1903-15
pubmed: 17989383
Nat Commun. 2022 Mar 4;13(1):1190
pubmed: 35246548
Nat Rev Immunol. 2019 Jun;19(6):383-397
pubmed: 30837674
Philos Trans R Soc Lond B Biol Sci. 2009 Jun 12;364(1523):1629-40
pubmed: 19414476
J Infect Dis. 1985 Jan;151(1):81-8
pubmed: 3965596
Nat Commun. 2019 Apr 10;10(1):1660
pubmed: 30971703
Science. 2019 Oct 25;366(6464):499-504
pubmed: 31649200
PLoS Pathog. 2012;8(7):e1002802
pubmed: 22829765
PLoS Biol. 2018 Aug 20;16(8):e2004974
pubmed: 30125272
Science. 2004 Jul 16;305(5682):371-6
pubmed: 15218094
Lancet. 2018 Mar 31;391(10127):1285-1300
pubmed: 29248255
Stat Med. 2006 May 15;25(9):1485-97
pubmed: 16158409
PLoS One. 2013 Jun 05;8(6):e65919
pubmed: 23755294
Nat Commun. 2021 Jul 14;12(1):4313
pubmed: 34262041
Nat Med. 2020 Nov;26(11):1691-1693
pubmed: 32929268
Emerg Infect Dis. 2018 Aug;24(8):1536-1540
pubmed: 30015611
Influenza Other Respir Viruses. 2021 Mar;15(2):235-244
pubmed: 33108707
Nat Med. 2019 Jun;25(6):962-967
pubmed: 31160818
Elife. 2014;3:e01914
pubmed: 24497547
Science. 2014 Nov 21;346(6212):996-1000
pubmed: 25414313
Nat Med. 2022 Feb;28(2):363-372
pubmed: 35177857
Bioinformatics. 2006 Feb 1;22(3):310-6
pubmed: 16303799
Int J Epidemiol. 2017 Apr 1;46(2):e16
pubmed: 26875566
mBio. 2020 Jan 21;11(1):
pubmed: 31964741
Sci Transl Med. 2015 Dec 2;7(316):316ra192
pubmed: 26631631
PLoS Pathog. 2020 Jul 23;16(7):e1008635
pubmed: 32702069
PLoS Biol. 2015 Mar 03;13(3):e1002082
pubmed: 25734701
Nat Commun. 2020 Sep 11;11(1):4566
pubmed: 32917903
Epidemics. 2017 Sep;20:84-93
pubmed: 28395850
Influenza Other Respir Viruses. 2016 Nov;10(6):518-524
pubmed: 27406695
Clin Infect Dis. 2019 May 2;68(10):1713-1717
pubmed: 30202873
Science. 2016 Nov 11;354(6313):722-726
pubmed: 27846599
Science. 2022 Jul 15;377(6603):eabq1841
pubmed: 35699621
PLoS Med. 2011 Jul;8(7):e1001051
pubmed: 21750666