Birth cohort relative to an influenza A virus's antigenic cluster introduction drives patterns of children's antibody titers.
Birth cohort relative to an influenza A virus's antigenic cluster introduction drives patterns of children's antibody titers.
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DOI：
10.1371/journal.ppat.1010317
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发表时间：
2022-03
期刊：
影响因子：
6.7
通讯作者：
Gordon A
中科院分区：
文献类型：
--
作者：
Brouwer AF;Balmaseda A;Gresh L;Patel M;Ojeda S;Schiller AJ;Lopez R;Webby RJ;Nelson MI;Kuan G;Gordon A
个体对甲型流感病毒株的抗体滴度是感染史、交叉反应性、免疫减弱和其他因素复杂相互作用的结果。仅从横断面数据就能弄清人群水平的体液免疫模式是如何随着年龄、日历年和出生队列的变化而变化的，这一直是一个挑战。我们分析了2006 - 2016年在尼加拉瓜进行的三项研究中来自260名儿童的1589份纵向血清样本。测定4株H3N2、1株H1N1和2株H1N1pdm的血凝抑制（HAI）效价。我们使用年龄-时期-队列模型框架评估了HAI滴度的时间模式。我们发现针对特定病毒的滴度取决于血清收集的日历年和出生队列，而不是年龄。滴度队列模式更好地描述了参与者的年龄相对于病毒抗原簇可能引入的年份，而不是年龄相对于菌株引入的年份或出生年份。这些群体效应可能是由群集引入后早期感染的可能性降低和年轻时更广泛的反应性抗体驱动的。H3N2和H1N1病毒在质量上具有不同的队列模式，对特定H3N2毒株滴度的队列模式在该病毒抗原簇引入前3年出生的儿童中达到峰值，对H1N1和H1N1pdm毒株滴度的队列模式在该病毒簇引入前1-2年出生的儿童中达到峰值，但在年龄较大的儿童中没有显著降低。最终，菌株循环和抗原簇引入的特定模式可能会驱动儿童群体水平的抗体滴度模式。人类对甲型流感病毒的抗体反应是复杂的，部分原因是这些病毒很容易变异以逃避我们的免疫系统。偶尔更大的基因变化可以建立一个新的病毒组，称为抗原簇，基于我们抗体反应的相似性。更好地了解我们的抗体反应如何随时间变化，可以改善疫苗接种策略，包括菌株选择，疫苗接种时间，每年接种疫苗是否最佳，以及疫苗接种反应随年龄的变化有多大。在这项研究中，我们研究了抗体反应如何随着时间的三个维度变化，即年龄、日历年和出生队列。正如预期的那样，抗体滴度取决于每种流感亚型传播的年份。我们还发现，当来自同一抗原簇的相关病毒首次传播时，抗体对病毒的反应取决于一个人的年龄，而不是特定病毒传播时。我们还发现证据表明，幼儿可能具有与尚未循环的菌株交叉反应的抗体，这可能表明他们的免疫系统正在产生广泛的抗体，这可能为抗原性优先性的可能机制提供信息。我们的结果揭示了新的动态抗体滴度水平。
An individual’s antibody titers to influenza A strains are a result of the complicated interplay between infection history, cross-reactivity, immune waning, and other factors. It has been challenging to disentangle how population-level patterns of humoral immunity change as a function of age, calendar year, and birth cohort from cross-sectional data alone. We analyzed 1,589 longitudinal sera samples from 260 children across three studies in Nicaragua, 2006–16. Hemagglutination inhibition (HAI) titers were determined against four H3N2 strains, one H1N1 strain, and two H1N1pdm strains. We assessed temporal patterns of HAI titers using an age–period–cohort modeling framework. We found that titers against a given virus depended on calendar year of serum collection and birth cohort but not on age. Titer cohort patterns were better described by participants’ ages relative to year of likely introduction of the virus’s antigenic cluster than by age relative to year of strain introduction or by year of birth. These cohort effects may be driven by a decreasing likelihood of early-life infection after cluster introduction and by more broadly reactive antibodies at a young age. H3N2 and H1N1 viruses had qualitatively distinct cohort patterns, with cohort patterns of titers to specific H3N2 strains reaching their peak in children born 3 years prior to that virus’s antigenic cluster introduction and with titers to H1N1 and H1N1pdm strains peaking for children born 1–2 years prior to cluster introduction but not being dramatically lower for older children. Ultimately, specific patterns of strain circulation and antigenic cluster introduction may drive population-level antibody titer patterns in children. The human antibody response to influenza A viruses is complex, in part because these viruses readily mutate to evade our immune systems. Occasional greater genetic changes can establish a new group of viruses, called an antigenic cluster, based on the similarity of our antibody responses. A better understanding of how our antibody responses change over time could improve vaccination strategies around strain selection, vaccination timing, whether yearly vaccination is optimal, and how much variability in vaccination response by age to expect. In this study, we examined how antibody responses change along three dimensions of time, namely age, calendar year, and birth cohort. As expected, antibody titers depended on what years each influenza subtype circulated. We also found that antibody responses to a virus depended on one’s age when a related virus from the same antigenic cluster first circulated, not when that specific virus circulated. We also find evidence young children may have antibodies that cross-react with strains that have not yet circulated, possibly indicating that their immune systems are creating a wide array of antibodies, which could inform possible mechanisms of antigenic seniority. Our results shed new light on the dynamics of antibody titer levels.
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DOI：
10.1097/inf.0000000000000944
发表时间：
2016-02
期刊：
The Pediatric infectious disease journal
影响因子：
--
作者：
Gresh L;Kuan G;Sanchez N;Azziz-Baumgartner E;Ojeda S;Melendez M;Lopez R;Martin ET;Widdowson MA;Bresee J;Harris E;Balmaseda A;Gordon A
通讯作者：
Gordon A
影响因子：
4.3
作者：
Hay, James A.;Minter, Amanda;Riley, Steven
通讯作者：
Riley, Steven
影响因子：
3
作者：
Anderson CS;McCall PR;Stern HA;Yang H;Topham DJ
通讯作者：
Topham DJ
DOI：
10.1038/s41572-018-0002-y
发表时间：
2018-06-28
期刊：
Nature reviews. Disease primers
影响因子：
--
作者：
Krammer F;Smith GJD;Fouchier RAM;Peiris M;Kedzierska K;Doherty PC;Palese P;Shaw ML;Treanor J;Webster RG;García-Sastre A
通讯作者：
García-Sastre A
DOI：
10.1126/science.1256427
发表时间：
2014-11-21
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Fonville JM;Wilks SH;James SL;Fox A;Ventresca M;Aban M;Xue L;Jones TC;Le NMH;Pham QT;Tran ND;Wong Y;Mosterin A;Katzelnick LC;Labonte D;Le TT;van der Net G;Skepner E;Russell CA;Kaplan TD;Rimmelzwaan GF;Masurel N;de Jong JC;Palache A;Beyer WEP;Le QM;Nguyen TH;Wertheim HFL;Hurt AC;Osterhaus ADME;Barr IG;Fouchier RAM;Horby PW;Smith DJ
通讯作者：
Smith DJ