<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3-mathml3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" article-type="research-article" dtd-version="1.3" xml:lang="EN">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1664-3224</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fimmu.2026.1764884</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Association of plasma ferritin and plasma iron at time of vaccination with the immune response to SARS-CoV-2 vaccination: a longitudinal cohort study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Pestoni</surname><given-names>Giulia</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2138306/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Project-administration" vocab-term-identifier="https://credit.niso.org/contributor-roles/project-administration/">Project administration</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Funding acquisition" vocab-term-identifier="https://credit.niso.org/contributor-roles/funding-acquisition/">Funding acquisition</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Menges</surname><given-names>Dominik</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/116243/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Funding acquisition" vocab-term-identifier="https://credit.niso.org/contributor-roles/funding-acquisition/">Funding acquisition</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Fenwick</surname><given-names>Craig</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1036645/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Scheuchzer</surname><given-names>Pornpimol</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Braun</surname><given-names>Julia</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Haile</surname><given-names>Sarah R.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1341615/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Formal analysis" vocab-term-identifier="https://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Ballouz</surname><given-names>Tala</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/961998/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Zeder</surname><given-names>Christophe</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/836508/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Stoffel</surname><given-names>Nicole U.</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/966561/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Zimmermann</surname><given-names>Michael B.</given-names></name>
<xref ref-type="aff" rid="aff7"><sup>7</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/979581/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Puhan</surname><given-names>Milo A.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/919552/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Funding acquisition" vocab-term-identifier="https://credit.niso.org/contributor-roles/funding-acquisition/">Funding acquisition</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Frei</surname><given-names>Anja</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1190667/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Moretti</surname><given-names>Diego</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/587373/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Funding acquisition" vocab-term-identifier="https://credit.niso.org/contributor-roles/funding-acquisition/">Funding acquisition</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &amp; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &amp; editing</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Project-administration" vocab-term-identifier="https://credit.niso.org/contributor-roles/project-administration/">Project administration</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="visualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/visualization/">Visualization</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label><institution>Nutrition Group, Swiss Distance University of Applied Sciences (FFHS)/University of Applied Sciences and Arts of Southern Switzerland (SUPSI)</institution>, <city>Zurich</city>,&#xa0;<country country="ch">Switzerland</country></aff>
<aff id="aff2"><label>2</label><institution>Department of Epidemiology, Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich (UZH)</institution>, <city>Zurich</city>,&#xa0;<country country="ch">Switzerland</country></aff>
<aff id="aff3"><label>3</label><institution>Service of Immunology and Allergy, Lausanne University Hospital (CHUV), University of Lausanne (UNIL)</institution>, <city>Lausanne</city>,&#xa0;<country country="ch">Switzerland</country></aff>
<aff id="aff4"><label>4</label><institution>Department of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, ETH Zurich</institution>, <city>Zurich</city>,&#xa0;<country country="ch">Switzerland</country></aff>
<aff id="aff5"><label>5</label><institution>Department of Health Sciences and Technology, Institute of Food, Nutrition and Health, ETH Zurich</institution>, <city>Zurich</city>,&#xa0;<country country="ch">Switzerland</country></aff>
<aff id="aff6"><label>6</label><institution>Nuffield Department of Orthopedics, Rheumatology and Musculoskeletal Medicine, Botnar Research Centre, University of Oxford</institution>, <city>Oxford</city>,&#xa0;<country country="gb">United Kingdom</country></aff>
<aff id="aff7"><label>7</label><institution>Medical Research Council Translational Immune Discovery Unit, MRC Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford</institution>, <city>Oxford</city>,&#xa0;<country country="gb">United Kingdom</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Diego Moretti, <email xlink:href="mailto:diego.moretti@ffhs.ch">diego.moretti@ffhs.ch</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-03-04">
<day>04</day>
<month>03</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>17</volume>
<elocation-id>1764884</elocation-id>
<history>
<date date-type="received">
<day>10</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>10</day>
<month>02</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>28</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Pestoni, Menges, Fenwick, Scheuchzer, Braun, Haile, Ballouz, Zeder, Stoffel, Zimmermann, Puhan, Frei and Moretti.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Pestoni, Menges, Fenwick, Scheuchzer, Braun, Haile, Ballouz, Zeder, Stoffel, Zimmermann, Puhan, Frei and Moretti</copyright-holder>
<license>
<ali:license_ref start_date="2026-03-04">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Recent studies have shown a link between iron status and immune response following infection or vaccination. We aimed to investigate whether plasma ferritin and plasma iron concentrations at time of vaccination were associated with the development and temporal decay of immune response to SARS-CoV-2 vaccination over 6 months.</p>
</sec>
<sec>
<title>Materials and methods</title>
<p>We used data from the Zurich SARS-CoV-2 Vaccine Cohort (n=572). Participants were recruited from a random sample stratified by age groups (18&#x2013;64 years, &gt;65 years) and vaccine types (Pfizer-BioNTech BNT162b2, Moderna mRNA-1273, Johnson &amp; Johnson JNJ-78436735). Iron parameters were measured at baseline (prior to vaccination), whereas different immunity markers were measured at baseline, 4 weeks, 6 weeks, 3 months, and 6 months. We investigated the association between plasma ferritin and plasma iron levels and immunity markers using linear mixed-effect models, and estimated half-life based on linear decay models.</p>
</sec>
<sec>
<title>Results</title>
<p>Plasma ferritin and plasma iron concentrations were within the normal physiological range, and the prevalence of iron deficiency (4.5%) and inflammation (2.3%) was low. For every 50 &#x3bc;g/L increase in plasma ferritin concentration, we observed a 5.2% increase in Anti-S IgG antibodies, and a 13.6-19.9% increase in neutralizing antibodies against the Ancestral, Delta, and Omicron BA1 viral variants. Similarly, the highest plasma ferritin quartile showed a 14.9% increase in Anti-S IgG antibodies, and a 47.1-82.2% increase in Anti-Ancestral, Anti-Delta, and Anti-Omicron neutralizing antibodies compared to the lowest quartile. Despite high concentrations at 6 months, shorter mean half-lives of Anti-S IgG antibodies were observed in the highest quartiles of plasma ferritin concentrations (Q3: 121.4 days; Q4: 109.8 days <italic>vs</italic>. Q1: 152.1 days). Plasma iron results were less consistent and generally no evidence for associations was found.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>In this predominantly iron-replete cohort, higher plasma ferritin at the time of vaccination was associated with stronger vaccination-induced humoral immune responses to SARS-CoV-2 over 6 months.</p>
</sec>
</abstract>
<kwd-group>
<kwd>antibody response</kwd>
<kwd>iron status</kwd>
<kwd>neutralizing antibody response</kwd>
<kwd>plasma ferritin</kwd>
<kwd>plasma iron</kwd>
<kwd>SARS-CoV-2</kwd>
<kwd>vaccination</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This study is part of Corona Immunitas research network, coordinated by the Swiss School of Public Health (SSPH+), and funded by fundraising of SSPH+ that includes funds of the Swiss Federal Office of Public Health and private funders (ethical guidelines for funding stated by SSPH+ were respected), funds of the Cantons of Switzerland (Vaud, Zurich, and Basel) and institutional funds of the Universities. Further funding specific for the Zurich SARS-CoV-2 Vaccine Cohort was received from the Uniscientia Foundation (Switzerland), from the Swiss Federal Office of Public Health, and the CoVICIS project (grant number 101046041) funded by the EU Horizon Europe Program. Additional funding specific for this study was obtained from the Foundation for the encouragement of Nutrition Research in Switzerland (SFEFS, project number 592). DMe received additional funding by the UZH Postdoc Grant (grant number FK-22-053). TB is additionally supported by a Moderna Global Fellowship award. The funders had no influence on the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
<counts>
<fig-count count="1"/>
<table-count count="6"/>
<equation-count count="0"/>
<ref-count count="38"/>
<page-count count="14"/>
<word-count count="9763"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Nutritional Immunology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>The COVID-19 global pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is estimated to have resulted in over 700 million people diagnosed, and over 7 million deaths by the end of 2024 (<xref ref-type="bibr" rid="B1">1</xref>). Vaccination is considered the most effective mitigation strategy to reduce disease severity during acute infection. Consequently, countries worldwide invested substantial resources into ensuring a rapid roll-out of SARS-CoV-2 vaccines and promoting their uptake within the population.</p>
<p>Iron deficiency remains a prominent nutritional deficiency and is one of the leading causes of years lived with disability worldwide (<xref ref-type="bibr" rid="B2">2</xref>). In Western Europe, it has been estimated that 40-55% of women of reproductive age have depleted iron stores, with 10-30% having iron deficiency (<xref ref-type="bibr" rid="B3">3</xref>). Iron deficiency can be divided into absolute and functional iron deficiency, the latter being characterized by hypoferremia and iron maldistribution, which can equally result in tissue and erythroid deficiency in a similar manner to absolute iron deficiency (<xref ref-type="bibr" rid="B4">4</xref>).</p>
<p>Iron status has been linked to the development of innate and acquired immunity in several studies. T cells from iron-deficient elderly individuals showed less proliferative capacity upon ex vivo stimulation with mitogens than those from iron-replete controls (<xref ref-type="bibr" rid="B5">5</xref>). Similarly, mitogenic stimulation of peripheral blood mononuclear cells (PBMCs) from iron-deficient children showed reduced IL-2 production (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B7">7</xref>). Conversely, iron supplementation has been shown to increase the number of total and mature T cells in iron-deficient children (<xref ref-type="bibr" rid="B7">7</xref>). Jabara et&#xa0;al. (<xref ref-type="bibr" rid="B8">8</xref>) reported that children presenting a mutation in the encoding region for transferrin receptor 1 (TfR1), which impairs iron acquisition, have severe immunodeficiency associated with reduced memory B cells, inhibited T and B cell proliferation ex vivo, and antibody class-switching, resulting in severe and sometimes fatal infections (<xref ref-type="bibr" rid="B8">8</xref>).</p>
<p>Recent studies suggest that iron deficiency also impairs immune response following vaccination (<xref ref-type="bibr" rid="B9">9</xref>&#x2013;<xref ref-type="bibr" rid="B11">11</xref>). In a randomized controlled trial in Kenyan infants, Stoffel et&#xa0;al. showed higher anti-measles IgG concentration and avidity in children receiving iron supplementation at time of vaccination (<xref ref-type="bibr" rid="B9">9</xref>). In a birth cohort of Kenyan newborns followed for 18 months, high hemoglobin at time of vaccination was associated with higher anti-diphtheria IgG, anti-pertussis IgG, and anti-pneumococcus serotype 19 IgG antibodies. Moderate to severe anemia and soluble transferrin receptor (sTfR) at time of vaccination were both risk factors for seronegativity against diphtheria and pneumococcus serotype 19 (<xref ref-type="bibr" rid="B9">9</xref>). In another study, patients with severe hypoferremia associated with a rare form of iron refractory anemia due to a mutation in the TMPRSS6 hepcidin regulation gene showed a lower vaccine-inducible antibody response than control individuals (<xref ref-type="bibr" rid="B10">10</xref>). Similarly, hypoferremia has been associated with a lower antibody response to measles vaccines compared to the antibody response in iron-sufficient controls (<xref ref-type="bibr" rid="B11">11</xref>).</p>
<p>Shortly after SARS-CoV-2 vaccines became available, a working group of the European Hematology Association issued an expert recommendation, advising to correct iron deficiency in individuals with hematologic conditions before the administration of the SARS-CoV-2 vaccines (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>). However, SARS-CoV-2 vaccines are remarkably protective even in populations where iron deficiency may be prevalent (<xref ref-type="bibr" rid="B14">14</xref>). This underscores the need for further research, particularly in exploring the immune response in more detail, including the response to more resistant variants, and characterizing speed and duration of the immune response after administration of SARS-CoV-2 vaccines (<xref ref-type="bibr" rid="B12">12</xref>). These have not been investigated systematically to date (<xref ref-type="bibr" rid="B13">13</xref>). Therefore, using data from a population-based, prospective cohort of SARS-CoV-2 vaccinated individuals, we aimed to investigate whether plasma ferritin and plasma iron concentrations at time of vaccination were associated with the development and temporal decay of markers of immune response to SARS-CoV-2 vaccination over 6 months.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Design and study population</title>
<p>The analyses were conducted using data and samples from the population-based, prospective Zurich SARS-CoV-2 Vaccine Cohort study (<xref ref-type="bibr" rid="B15">15</xref>). Participants were recruited from a random sample of individuals receiving a SARS-CoV-2 vaccine at the reference vaccination center of the Canton of Zurich in Switzerland (Corona Center of the University of Zurich). The study sample was stratified by two age groups (18&#x2013;64 years, 65 years and older) and by the three vaccine types available in Switzerland during the recruitment period (Pfizer-BioNTech BNT162b2, Moderna mRNA-1273, Johnson &amp; Johnson JNJ-78436735). The vaccines were approved by the Swiss Agency for Therapeutic Products between December 2020 and March 2021 (<xref ref-type="bibr" rid="B16">16</xref>). Recruitment of study participants took place between March and July 2021 for individuals receiving an mRNA vaccine (BNT162b2 or mRNA-1273), and between October 2021 and January 2022 for individuals receiving the JNJ-78436735 adenovirus viral vector vaccine. Individuals vaccinated with an mRNA vaccine received two vaccine doses approximately 4 weeks apart. Individuals vaccinated with the JNJ-78436735 vaccine received one vaccine dose. The present study included up to 6 months of follow-up. While cohort follow-up continued beyond this time period, we did not include later timepoints in this study in light of our primary research question and to minimize the influence of booster vaccinations and breakthrough infections due to the Omicron SARS-CoV-2 variant arriving in Switzerland in December 2021.</p>
<p>Exclusion criteria for participation in the Zurich SARS-CoV-2 Vaccine Cohort study were: younger than 18 years, unable to follow study procedures, insufficient knowledge of the German language, prior SARS-CoV-2 vaccination in another center, and primary residence outside of the Canton of Zurich. Additionally, to increase representativeness, individuals registering as belonging to one of the following groups at the beginning of the vaccination campaign were excluded, since they represent specific population groups with priority access to vaccination: health care workers, caretakers of high-risk individuals, individuals living in communal facilities, and individuals with high-risk diseases (i.e., advanced stages of diseases such as decompensated heart or liver failure). If these individuals were registered as belonging to a regular priority group, they were eligible for inclusion. Additionally, for this analysis, participants were excluded if blood samples for iron status measurements were not available. The final study population included in the present analyses consisted of 572 individuals. A participant flow diagram is presented in <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure S1</bold></xref>.</p>
<p>The Research Electronic Data Capture platform (REDCap) was used for data collection. All procedures were approved by the ethics committee of the Canton of Zurich (BASEC 2021-00273) and written informed consent was obtained from all participants. The study was prospectively registered at the ISRCTN registry (ISRCTN 15499304).</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Self-reported information</title>
<p>Participants were asked to complete a self-administered electronic questionnaire at baseline and at 4 weeks, 6 weeks, and approximately 3 months and 6 months after baseline. The questionnaire included questions on sociodemographic factors, smoking history, medical history, presence of comorbidities (i.e., hypertension, diabetes, cardiovascular disease, chronic respiratory disease, chronic kidney disease, cancer, or immunosuppression), SARS-CoV-2 exposure- and infection-related information, and vaccination-related information.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Collection and isolation of plasma</title>
<p>Collection of peripheral venous blood samples was performed by trained personnel at baseline and at 4 weeks, 6 weeks, 3 months, and 6 months after baseline. The timing of blood collection was not standardized in the Zurich SARS-CoV-2 Vaccine Cohort Study. During the baseline and the 4 weeks visit (for participants receiving two doses of an mRNA vaccine), blood samples were collected immediately before vaccination. Blood samples were collected in K2-EDTA vacutainer tubes and subsequently centrifuged to obtain plasma. Plasma aliquots were then frozen and stored until further analyses.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Measurements of iron parameters</title>
<p>Plasma ferritin, sTfR, retinol-binding protein (RBP), high-sensitive C-reactive protein (CRP) and alpha(1)-acid glycoprotein (AGP) were measured in the baseline samples using a combined sandwich enzyme-linked immunosorbent assay (<xref ref-type="bibr" rid="B17">17</xref>). Iron deficiency was defined as ferritin &lt; 25 &#x3bc;g/L (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B19">19</xref>). Risk of iron overload was defined as ferritin &gt; 150 &#x3bc;g/L for women of reproductive age and ferritin &gt; 200 &#x3bc;g/L for men and post-menopausal women, according to guidelines of the World Health Organization (<xref ref-type="bibr" rid="B20">20</xref>). Total body iron stores were calculated based on sTfR and ferritin using the method by Cook at al (<xref ref-type="bibr" rid="B21">21</xref>). Systemic inflammation was defined as CRP &#x2265; 5 mg/L or AGP &#x2265; 1 g/L.</p>
<p>Plasma iron was measured in the baseline samples in duplicates by inductively coupled plasma-mass spectrometry (ICP-MS; Q-ICP-MS iCap RQ, Thermo Scientific). Plasma iron concentrations were corrected for hemoglobin iron potentially present in the samples as consequence of hemolysis. The degree of hemolysis in plasma samples was determined by spectrophotometric measurement at 414 nm and compared to a calibration curve prepared from plasma and hemolyzed whole blood (<xref ref-type="bibr" rid="B22">22</xref>). Hemolysis was additionally checked visually using a color scale. Plasma samples were excluded when too little volume was available for measurements (n=2), when plasma iron values were implausibly high due to hemolysis (n=5), when correction for hemoglobin was impossible (n=1), and when the discrepancy between the duplicate plasma iron measurements was &gt; 40% (n=2). This resulted in a study sample of n=562 individuals for plasma iron analyses (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure S1</bold></xref>).</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Measurements of spike-specific IgA and IgG antibodies and neutralization assays</title>
<p>Spike (S)-specific IgA and IgG antibody measurements were performed at baseline, and at 4 weeks, 6 weeks, 3 months, and 6 months after baseline. Plasma samples were thawed, and levels of S-specific IgA and IgG were measured by Luminex assay. Measurement procedures were described in detail elsewhere (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>). Antibody levels were reported as mean fluorescence intensity (MFI) ratios, which was calculated as the MFI in the sample divided by the MFI in seronegative control samples. The lower limit of MFI ratios was restricted to 1, representing equal fluorescence intensity as negative control samples. Seropositivity was defined as MFI ratios of &gt; 6.5 for IgA and &gt; 6.0 for IgG (<xref ref-type="bibr" rid="B24">24</xref>).</p>
<p>Measurements of neutralizing antibodies (NAb) were performed at 4 weeks, 3 months, and 6 months after baseline in a subsample of the study population (n=214). Frozen plasma samples were thawed, and the presence of SARS-CoV-2 NAb was assessed using a virus-and cell-free, Luminex-based assay described in detail elsewhere (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B25">25</xref>). Based on the measurements, a half maximal inhibitory concentration serum dilution (IC<sub>50</sub>) was calculated, with an IC<sub>50</sub> of 50 determined as a specificity cutoff to minimize the detection of false-positive samples.</p>
</sec>
<sec id="s2_6">
<label>2.6</label>
<title>Statistical analysis</title>
<p>Descriptive statistics were used to describe the study population. Continuous variables were reported as mean (standard deviation, SD) or as geometric mean (95% confidence interval, CI) when not normally distributed.</p>
<p>To investigate the longitudinal association between plasma ferritin or plasma iron levels at time of vaccination and antibody or NAb levels as markers of immune response, linear mixed-effect models were fitted with a random intercept for individuals. Iron parameters were included either as continuous variables or participants were divided into quartiles according to concentrations of iron parameters at time of vaccination. Models including plasma&#xa0;ferritin were adjusted for antibody levels at baseline, vaccine type and number of vaccine doses received, time point of&#xa0;study visit, re-exposure at study visit (defined as a diagnosed SARS-CoV-2 infection or subsequent additional vaccination), CRP, AGP, RBP, age, sex, and smoking status. The timing of blood collection across quartiles of plasma iron was balanced (Q1: 11:59, Q2: 12:11, Q3: 12:26, Q4: 12:07). Despite this, models including plasma iron were further adjusted for time of the day of study visit (as numeric time), as plasma iron concentrations show circadian variations (<xref ref-type="bibr" rid="B26">26</xref>).</p>
<p>We also investigated the association of plasma ferritin and plasma iron levels with antibody or NAb levels at single time points of study visits (i.e., at 4 weeks, 6 weeks, 3 months, and 6 months for Anti-S IgA and Anti-S IgG; at 4 weeks, 3 months, and 6 months for Anti-Ancestral, Anti-Delta, and Anti-Omicron BA1 viral variant NAb). Models including plasma ferritin were adjusted for antibody levels at baseline, vaccine type and number of vaccine doses received, re-exposure at corresponding time point of study visit, CRP, AGP, RBP, age, sex, and smoking status. Models including plasma iron were further adjusted for time of the day of study visit.</p>
<p>Participants with missing information on smoking status and missing data points on immunity markers at any time point were excluded from statistical modeling, and all immunity markers were logarithmically transformed using log10. When included as continuous variable in the models, plasma ferritin was rescaled to reflect changes in immunity markers per 50 &#x3bc;g/L increase. The original scale was used for plasma iron, reflecting changes in immunity markers per 1 &#x3bc;g/mL increase. Previous studies on influenza vaccines have reported that antibody levels prior to vaccination affect the post-vaccination immune response (<xref ref-type="bibr" rid="B27">27</xref>). Therefore, we adjusted our models for baseline antibody levels. Baseline Anti-S IgA level was used in models investigating Anti-S IgA, whereas baseline Anti-S IgG level was used in models investigating Anti-S IgG. Since no NAb measurements were performed at baseline, the baseline Anti-S IgG level was used to adjust models investigating Anti-Ancestral, Anti-Delta, and Anti-Omicron NAb, as this was considered the most robust measure of the strength of the immune response.</p>
<p>As sensitivity analyses, all models were fitted by adding comorbidities as adjusting factors, by excluding participants with inflammation, and by excluding CRP and AGP as adjusting factors. In addition, analyses of NAb were adjusted for seropositivity at baseline and knowledge of a prior infection, rather than for baseline Anti-S IgG level.</p>
<p>To estimate decay times, we followed the procedure described by Menges et&#xa0;al. (<xref ref-type="bibr" rid="B23">23</xref>). The maximum antibody concentration defined as the maximum antibody level between week 4, week 6, and month 3, was determined for each participant. The data were then restricted to the corresponding time point and all subsequent time points, with the time axis rescaled to the time since maximum antibody concentration so that the data represented a descending slope of antibody levels (decay curve). In these analyses, participants never testing positive for the respective immunity marker were excluded. Additionally, time points in which participants reported a re-exposure as well as time points in which antibody levels increased (post-vaccination or potential undiagnosed SARS-CoV-2 infection) were also excluded. To investigate the decay of immunity markers by plasma ferritin and plasma iron levels at time of vaccination, univariable and multivariable linear mixed-effect models with a random intercept for individuals were fitted. Univariable linear mixed-effect models included an interaction term between days since maximum antibody concentration and plasma ferritin or plasma iron quartiles. Multivariable linear mixed effect models were further adjusted for maximum antibody concentration, vaccine type and number of vaccine doses received, CRP, AGP, RBP, age, sex, and smoking status for plasma ferritin and additionally adjusted for time of the day of study visit for plasma iron. All immunity markers were logarithmically transformed using the natural logarithm. The half-life in days was then calculated using the following formula:</p>
<p>&#x2003;&#x2003;&#x2003;&#x2003;&#x2003;&#x2003;&#x2003;Half-life = log (0.5)/&#x3b2;</p>
<p>where &#x3b2; is the model-derived estimate of the interaction term between days since maximum antibody concentration and plasma ferritin or plasma iron quartiles. 95% CI were calculated using the delta method and p-values derived with t-statistics using the Satterthwaite&#x2019;s approximation method for degrees of freedom. Half-life for Anti-Omicron NAb could not be estimated.</p>
<p>Statistical analyses were performed using the R software (version 4.4.1 for Windows). The following packages were used: <italic>car, data.table, DescTools, dplyr, ggplot2, gridExtra, hms, lme4, lmerTest, msm, plyr, string</italic>, and <italic>tidyr</italic>. A p-value of &lt; 0.05 was considered as statistically significant in all analyses.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<p>Out of 572 participants, 44.1% were male (<xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>). The mean age was 56.0 years (SD 18.1), and the mean body mass index (BMI) was 24.2 kg/m<sup>2</sup> (SD 3.9). More than half of the participants were non-smokers (56.5%) and almost one third had at least one reported comorbidity (27.6%). Most participants received 2 doses of an mRNA vaccine (Pfizer-BioNTech BNT162b2 or Moderna mRNA-1273, 68.2%). Seropositivity at baseline (defined as MFI ratio &gt; 6.5 for IgA or MFI ratio &gt; 6.0 for IgG antibodies), was 11.5% in the overall study population, and 8.3%, 10.4% and 17.0%, respectively, in participants vaccinated with BNT162b2, mRNA-1273, and JNJ-78436735. Re-exposure at 6 months was 12.6% in the overall study population, and 1.9%, 3.5% and 37.0% respectively in participants vaccinated with BNT162b2, mRNA-1273, JNJ-78436735.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Characteristics and antibody responses of participants of the Zurich SARS-CoV-2 vaccine cohort study overall and by sex and age group (n = 572).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Participants' characteristics</th>
<th valign="middle" align="center">Overall</th>
<th valign="middle" colspan="2" align="center">Sex</th>
<th valign="middle" colspan="2" align="center">Age group</th>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="center">Males</td>
<td valign="middle" align="center">Females</td>
<td valign="middle" align="center">18&#x2013;64 years</td>
<td valign="middle" align="center">65+ years</td>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="center">n = 572</td>
<td valign="middle" align="center">n = 252</td>
<td valign="middle" align="center">n = 320</td>
<td valign="middle" align="center">n = 307</td>
<td valign="middle" align="center">n = 265</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" colspan="6" align="left">Sex, n (%)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Male</td>
<td valign="middle" align="center">252 (44.1)</td>
<td valign="middle" align="center">252 (100)</td>
<td valign="middle" align="center">0 (0.0)</td>
<td valign="middle" align="center">145 (47.2)</td>
<td valign="middle" align="center">107 (40.4)</td>
</tr>
<tr>
<td valign="middle" align="left">Age (years)</td>
<td valign="middle" align="center">56.0 (18.1)</td>
<td valign="middle" align="center">55.3 (18.3)</td>
<td valign="middle" align="center">56.6 (17.9)</td>
<td valign="middle" align="center">41.7 (11.6)</td>
<td valign="middle" align="center">72.6 (6.5)</td>
</tr>
<tr>
<td valign="middle" align="left">BMI (kg/m<sup>2</sup>)</td>
<td valign="middle" align="center">24.2 (3.9)</td>
<td valign="middle" align="center">25.0 (3.5)</td>
<td valign="middle" align="center">23.5 (4.1)</td>
<td valign="middle" align="center">23.8 (3.7)</td>
<td valign="middle" align="center">24.6 (4.1)</td>
</tr>
<tr>
<td valign="middle" colspan="6" align="left">Smoking status, n (%)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Non-smoker</td>
<td valign="middle" align="center">323 (56.5)</td>
<td valign="middle" align="center">136 (54.0)</td>
<td valign="middle" align="center">187 (58.4)</td>
<td valign="middle" align="center">176 (57.3)</td>
<td valign="middle" align="center">147 (55.5)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Ex-smoker</td>
<td valign="middle" align="center">138 (24.1)</td>
<td valign="middle" align="center">70 (27.8)</td>
<td valign="middle" align="center">68 (21.2)</td>
<td valign="middle" align="center">61 (19.9)</td>
<td valign="middle" align="center">77 (29.1)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Smoker</td>
<td valign="middle" align="center">103 (18.0)</td>
<td valign="middle" align="center">43 (17.1)</td>
<td valign="middle" align="center">60 (18.8)</td>
<td valign="middle" align="center">66 (21.5)</td>
<td valign="middle" align="center">37 (14.0)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Missing</td>
<td valign="middle" align="center">8 (1.4)</td>
<td valign="middle" align="center">3 (1.2)</td>
<td valign="middle" align="center">5 (1.6)</td>
<td valign="middle" align="center">4 (1.3)</td>
<td valign="middle" align="center">4 (1.5)</td>
</tr>
<tr>
<td valign="middle" align="left">Comorbidities, n (%)</td>
<td valign="middle" align="center">158 (27.6)</td>
<td valign="middle" align="center">73 (29.0)</td>
<td valign="middle" align="center">85 (26.6)</td>
<td valign="middle" align="center">22 (7.2)</td>
<td valign="middle" align="center">136 (51.3)</td>
</tr>
<tr>
<td valign="middle" colspan="6" align="left">Vaccine type and dose, n (%)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;BNT162b2&#x2013;2 doses</td>
<td valign="middle" align="center">202 (35.3)</td>
<td valign="middle" align="center">91 (36.1)</td>
<td valign="middle" align="center">111 (34.7)</td>
<td valign="middle" align="center">102 (33.2)</td>
<td valign="middle" align="center">100 (37.7)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;mRNA-1273&#x2013;2 doses</td>
<td valign="middle" align="center">188 (32.9)</td>
<td valign="middle" align="center">79 (31.3)</td>
<td valign="middle" align="center">109 (34.1)</td>
<td valign="middle" align="center">89 (29.0)</td>
<td valign="middle" align="center">99 (37.4)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;BNT162b2/mRNA-1273&#x2013;1 dose</td>
<td valign="middle" align="center">17 (3.0)</td>
<td valign="middle" align="center">5 (2.0)</td>
<td valign="middle" align="center">12 (3.8)</td>
<td valign="middle" align="center">13 (4.2)</td>
<td valign="middle" align="center">4 (1.5)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;JNJ-78436735&#x2013;1 dose</td>
<td valign="middle" align="center">165 (28.8)</td>
<td valign="middle" align="center">77 (30.6)</td>
<td valign="middle" align="center">88 (27.5)</td>
<td valign="middle" align="center">103 (33.6)</td>
<td valign="middle" align="center">62 (23.4)</td>
</tr>
<tr>
<td valign="middle" colspan="6" align="left">Anti-S IgA at baseline</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;MFI ratio</td>
<td valign="middle" align="center">1.5 (1.4-1.6)</td>
<td valign="middle" align="center">1.5 (1.5-1.5)</td>
<td valign="middle" align="center">1.5 (1.5-1.5)</td>
<td valign="middle" align="center">1.5 (1.5-1.5)</td>
<td valign="middle" align="center">1.4 (1.4-1.4)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Positive, n (%)</td>
<td valign="middle" align="center">46 (8.0)</td>
<td valign="middle" align="center">19 (7.5)</td>
<td valign="middle" align="center">27 (8.4)</td>
<td valign="middle" align="center">27 (8.8)</td>
<td valign="middle" align="center">19 (7.2)</td>
</tr>
<tr>
<td valign="middle" colspan="6" align="left">Anti-S IgG at baseline</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;MFI ratio</td>
<td valign="middle" align="center">1.4 (1.3-1.6)</td>
<td valign="middle" align="center">1.5 (1.5-1.5)</td>
<td valign="middle" align="center">1.4 (1.4-1.4)</td>
<td valign="middle" align="center">1.6 (1.6-1.6)</td>
<td valign="middle" align="center">1.3 (1.3-1.3)</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Positive, n (%)</td>
<td valign="middle" align="center">52 (9.1)</td>
<td valign="middle" align="center">26 (10.3)</td>
<td valign="middle" align="center">26 (8.1)</td>
<td valign="middle" align="center">35 (11.4)</td>
<td valign="middle" align="center">17 (6.4)</td>
</tr>
<tr>
<td valign="middle" align="left">Re-exposure at 6 months, n (%)</td>
<td valign="middle" align="center">72 (12.6)</td>
<td valign="middle" align="center">32 (12.7)</td>
<td valign="middle" align="center">40 (12.5)</td>
<td valign="middle" align="center">54 (17.6)</td>
<td valign="middle" align="center">18 (6.8)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Continuous variables are given as mean (SD) or geometric mean (95% CI), categorical variables as n (%).</p></fn>
<fn>
<p>Comorbidities included hypertension, diabetes, cardiovascular disease, respiratory disease, chronic kidney disease, cancer, and immunosuppression.</p></fn>
<fn>
<p>BMI, body mass index; CI, confidence interval; MFI, mean fluorescence intensity; NAb, neutralizing antibodies; SD, standard deviation.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Plasma ferritin concentrations (geometric mean [95% CI]: 88.1 &#x3bc;g/L [83.4-93.0]) and plasma iron concentrations (mean [SD]: 0.82 &#x3bc;g/mL [0.33]) were in the normal physiological range (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>). Iron deficiency was generally low, with prevalence higher in females (7.8%) than in males (0.4%). The prevalence of iron deficiency in women of reproductive age (&lt; 50 years) was 17.5%, whereas the prevalence in females in the age group 18&#x2013;64 years was 14.8%. The risk of iron overload was also low. Out of 572 participants, 4 women of reproductive age had a ferritin concentration &gt; 150 &#x3bc;g/L and 46 men or post-menopausal women had a ferritin concentration &gt; 200 &#x3bc;g/L. Of these, 7&#xa0;participants had a ferritin concentration &gt; 250 &#x3bc;g/L. In the overall study population, the mean sTfR was 2.72 mg/L (SD 1.30), and the mean body iron stores were 11.7 mg/Kg (SD 3.7). Prevalence of inflammation was also low (2.3%).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Iron status of participants of the Zurich SARS-CoV-2 vaccine cohort study overall and by sex and age group (n = 572).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Iron and inflammatory markers</th>
<th valign="middle" align="center">Overall</th>
<th valign="middle" colspan="2" align="center">Sex</th>
<th valign="middle" colspan="2" align="center">Age group</th>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="left"/>
<td valign="middle" align="center">Males</td>
<td valign="middle" align="center">Females</td>
<td valign="middle" align="center">18&#x2013;64 years</td>
<td valign="middle" align="center">65+ years</td>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="center">n = 572</td>
<td valign="middle" align="center">n = 252</td>
<td valign="middle" align="center">n = 320</td>
<td valign="middle" align="center">n = 307</td>
<td valign="middle" align="center">n = 265</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">Plasma ferritin (&#x3bc;g/L)</td>
<td valign="middle" align="center">88.1 (83.4-93.0)</td>
<td valign="middle" align="center">115.3 (108.3-122.8)</td>
<td valign="middle" align="center">71.2 (66.0-76.8)</td>
<td valign="middle" align="center">75.9 (69.9-82.3)</td>
<td valign="middle" align="center">104.7 (98.3-111.5)</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron (&#x3bc;g/mL)</td>
<td valign="middle" align="center">0.82 (0.33)</td>
<td valign="middle" align="center">0.82 (0.35)</td>
<td valign="middle" align="center">0.82 (0.32)</td>
<td valign="middle" align="center">0.84 (0.33)</td>
<td valign="middle" align="center">0.80 (0.33)</td>
</tr>
<tr>
<td valign="middle" align="left">Iron deficiency, n (%)</td>
<td valign="middle" align="center">26 (4.5)</td>
<td valign="middle" align="center">1 (0.4)</td>
<td valign="middle" align="center">25 (7.8)</td>
<td valign="middle" align="center">24 (7.8)</td>
<td valign="middle" align="center">2 (0.8)</td>
</tr>
<tr>
<td valign="middle" align="left">Soluble transferrin receptor (mg/L)</td>
<td valign="middle" align="center">2.72 (1.30)</td>
<td valign="middle" align="center">2.66 (1.41)</td>
<td valign="middle" align="center">2.77 (1.20)</td>
<td valign="middle" align="center">2.79 (1.28)</td>
<td valign="middle" align="center">2.65 (1.31)</td>
</tr>
<tr>
<td valign="middle" align="left">Body iron stores (mg/Kg)</td>
<td valign="middle" align="center">11.7 (3.7)</td>
<td valign="middle" align="center">13.0 (3.5)</td>
<td valign="middle" align="center">10.7 (3.6)</td>
<td valign="middle" align="center">11.0 (4.0)</td>
<td valign="middle" align="center">12.5 (3.2)</td>
</tr>
<tr>
<td valign="middle" align="left">Retinol binding protein (&#x3bc;mol/L)</td>
<td valign="middle" align="center">1.03 (0.99-1.08)</td>
<td valign="middle" align="center">1.06 (1.00-1.14)</td>
<td valign="middle" align="center">1.01 (0.96-1.06)</td>
<td valign="middle" align="center">1.00 (0.95-1.06)</td>
<td valign="middle" align="center">1.07 (1.00-1.14)</td>
</tr>
<tr>
<td valign="middle" align="left">CRP (mg/L)</td>
<td valign="middle" align="center">0.44 (0.39-0.49)</td>
<td valign="middle" align="center">0.43 (0.37-0.51)</td>
<td valign="middle" align="center">0.44 (0.38-0.51)</td>
<td valign="middle" align="center">0.33 (0.28-0.38)</td>
<td valign="middle" align="center">0.61 (0.52-0.71)</td>
</tr>
<tr>
<td valign="middle" align="left">AGP (g/L)</td>
<td valign="middle" align="center">0.46 (0.18)</td>
<td valign="middle" align="center">0.45 (0.19)</td>
<td valign="middle" align="center">0.47 (0.17)</td>
<td valign="middle" align="center">0.46 (0.17)</td>
<td valign="middle" align="center">0.46 (0.20)</td>
</tr>
<tr>
<td valign="middle" align="left">Inflammation, n (%)</td>
<td valign="middle" align="center">13 (2.3)</td>
<td valign="middle" align="center">7 (2.8)</td>
<td valign="middle" align="center">6 (1.9)</td>
<td valign="middle" align="center">0 (0.0)</td>
<td valign="middle" align="center">13 (4.9)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Continuous variables are given as mean (SD) or geometric mean (95% CI), categorical variables as n (%).</p></fn>
<fn>
<p>Plasma iron values were based on a study sample of n = 562.</p></fn>
<fn>
<p>Iron deficiency was defined as plasma ferritin &lt; 25 &#x3bc;g/L.</p></fn>
<fn>
<p>Inflammation was defined as CRP &#x2265; 5 mg/L or AGP &#x2265; 1 g/L.</p></fn>
<fn>
<p>AGP, alpha(1)-acid glycoprotein; CI, confidence interval; CRP, c-reactive protein; SD, standard deviation.</p></fn>
</table-wrap-foot>
</table-wrap>
<p><xref ref-type="table" rid="T3"><bold>Tables&#xa0;3</bold></xref>, <xref ref-type="table" rid="T4"><bold>4</bold></xref> show results of linear mixed-effect models exploring the longitudinal association of antibody and NAb levels with plasma ferritin and plasma iron, respectively, over 6 months. We found significant positive associations between plasma ferritin concentration at time of vaccination and antibody levels as well as NAb levels in both continuous and categorical analyses (<xref ref-type="table" rid="T3"><bold>Table 3</bold></xref>). For every 50 &#x3bc;g/L increase in plasma ferritin concentration, we observed a 5.2% increase in Anti-S IgG antibodies, a 13.6% increase in Anti-Ancestral NAb, a 19.9% increase in Anti-Delta NAb, and a 16.7% increase in Anti-Omicron NAb over 6 months. Similarly, when exploring quartiles of plasma ferritin levels, individuals in the highest quartile (corresponding to a plasma ferritin level range of 141.0-250.0 &#x3bc;g/L) showed a 14.9% higher immune response for Anti-S IgG antibodies, and a 47.1%, 82.2%, and 75.1% higher immune response for Anti-Ancestral NAb, Anti-Delta NAb, and Anti-Omicron NAb, respectively, compared to those in the lowest quartile. We found no evidence for an association between plasma ferritin levels and Anti-S IgA antibodies.</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Longitudinal associations between plasma ferritin levels prior to vaccination and different immunity markers over 6 months.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<td valign="middle" align="left">Plasma ferritin</td>
<td valign="middle" colspan="3" align="center">Anti-S IgA</td>
<td valign="middle" colspan="3" align="center">Anti-S IgG</td>
<td valign="middle" colspan="3" align="center">Anti-Ancestral NAb</td>
<td valign="middle" colspan="3" align="center">Anti-Delta NAb</td>
<td valign="middle" colspan="3" align="center">Anti-Omicron NAb</td>
</tr>
<tr>
<td valign="middle" align="left"/>
<td valign="middle" align="center">Exp (&#x3b2;)</td>
<td valign="middle" align="center">&#x3b2;</td>
<td valign="middle" align="center">95%CI</td>
<td valign="middle" align="center">Exp (&#x3b2;)</td>
<td valign="middle" align="center">&#x3b2;</td>
<td valign="middle" align="center">95%CI</td>
<td valign="middle" align="center">Exp (&#x3b2;)</td>
<td valign="middle" align="center">&#x3b2;</td>
<td valign="middle" align="center">95%CI</td>
<td valign="middle" align="center">Exp (&#x3b2;)</td>
<td valign="middle" align="center">&#x3b2;</td>
<td valign="middle" align="center">95%CI</td>
<td valign="middle" align="center">Exp (&#x3b2;)</td>
<td valign="middle" align="center">&#x3b2;</td>
<td valign="middle" align="center">95%CI</td>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="16" align="left">Continuous analysis</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin</td>
<td valign="middle" align="center">1.023</td>
<td valign="middle" align="center">0.010</td>
<td valign="middle" align="center">-0.022;0.042</td>
<td valign="middle" align="center">1.052</td>
<td valign="middle" align="center">0.022</td>
<td valign="middle" align="center">0.009;0.035</td>
<td valign="middle" align="center">1.136</td>
<td valign="middle" align="center">0.055</td>
<td valign="middle" align="center">0.006;0.105</td>
<td valign="middle" align="center">1.199</td>
<td valign="middle" align="center">0.079</td>
<td valign="middle" align="center">0.028;0.702</td>
<td valign="middle" align="center">1.167</td>
<td valign="middle" align="center">0.067</td>
<td valign="middle" align="center">0.017;0.118</td>
</tr>
<tr>
<th valign="middle" colspan="16" align="left">Analysis by quartiles</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Q1 (4.3-62.1 &#x3bc;g/L)</td>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Q2 (62.2-96.3 &#x3bc;g/L)</td>
<td valign="middle" align="center">1.035</td>
<td valign="middle" align="center">0.015</td>
<td valign="middle" align="center">-0.081;0.111</td>
<td valign="middle" align="center">0.999</td>
<td valign="middle" align="center">0.000</td>
<td valign="middle" align="center">-0.040;0.040</td>
<td valign="middle" align="center">0.909</td>
<td valign="middle" align="center">-0.041</td>
<td valign="middle" align="center">-0.176;0.094</td>
<td valign="middle" align="center">1.017</td>
<td valign="middle" align="center">0.007</td>
<td valign="middle" align="center">-0.130;0.146</td>
<td valign="middle" align="center">1.020</td>
<td valign="middle" align="center">0.009</td>
<td valign="middle" align="center">-0.128;0.146</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Q3 (96.4-140.9 &#x3bc;g/L)</td>
<td valign="middle" align="center">0.980</td>
<td valign="middle" align="center">-0.009</td>
<td valign="middle" align="center">-0.105;0.088</td>
<td valign="middle" align="center">1.036</td>
<td valign="middle" align="center">0.015</td>
<td valign="middle" align="center">-0.025;0.055</td>
<td valign="middle" align="center">0.967</td>
<td valign="middle" align="center">-0.015</td>
<td valign="middle" align="center">-0.154;0.126</td>
<td valign="middle" align="center">1.083</td>
<td valign="middle" align="center">0.035</td>
<td valign="middle" align="center">-0.108;0.178</td>
<td valign="middle" align="center">1.000</td>
<td valign="middle" align="center">0.000</td>
<td valign="middle" align="center">-0.141;0.142</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Q4 (141.0-250.0 &#x3bc;g/L)</td>
<td valign="middle" align="center">1.142</td>
<td valign="middle" align="center">0.058</td>
<td valign="middle" align="center">-0.047;0.163</td>
<td valign="middle" align="center">1.149</td>
<td valign="middle" align="center">0.060</td>
<td valign="middle" align="center">0.017;0.104</td>
<td valign="middle" align="center">1.471</td>
<td valign="middle" align="center">0.168</td>
<td valign="middle" align="center">0.001;0.334</td>
<td valign="middle" align="center">1.822</td>
<td valign="middle" align="center">0.261</td>
<td valign="middle" align="center">0.090;0.431</td>
<td valign="middle" align="center">1.751</td>
<td valign="middle" align="center">0.243</td>
<td valign="middle" align="center">0.074;0.411</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Results were derived from linear mixed-effect models, using a random intercept for individuals and antibody or NAb levels as outcomes; models were adjusted for antibody level at baseline, vaccine type and number of vaccine doses received, time point of study visit, re-exposure at study visit, CRP, AGP, RBP, age, sex, smoking status. Complete results are presented in <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Tables S1</bold></xref> and <xref ref-type="supplementary-material" rid="SM1"><bold>S2</bold></xref>.</p></fn>
<fn>
<p>Coefficients &#x3b2; are on the log10 scale; exp(&#x3b2;), i.e. 10<sup>&#x3b2;</sup>, represents the multiplicative factor changes in antibody or NAb levels associated with a 50 &#x3bc;g/L increase in plasma ferritin levels in continuous analyses or compared to plasma ferritin Q1 in categorical analyses.</p></fn>
<fn>
<p>Models were based on a study sample of n=563 for Anti-S IgA, n=563 for Anti-S IgG, n=212 for Anti-Ancestral NAb, n=212 for Anti-Delta NAb, n=212 for Anti-Omicron Nab.</p></fn>
<fn>
<p>AGP, alpha(1)-acid glycoprotein; CI, confidence intervals; CRP, c-reactive protein; NAb, neutralizing antibodies; Q, quartile; RBP, retinol binding protein.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Longitudinal associations between plasma iron levels prior to vaccination and different immunity markers over 6 months.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Plasma iron</th>
<th valign="middle" colspan="3" align="center">Anti-S IgA</th>
<th valign="middle" colspan="3" align="center">Anti-S IgG</th>
<th valign="middle" colspan="3" align="center">Anti-Ancestral NAb</th>
<th valign="middle" colspan="3" align="center">Anti-Delta NAb</th>
<th valign="middle" colspan="3" align="center">Anti-Omicron NAb</th>
</tr>
<tr>
<th valign="middle" align="center"/>
<th valign="middle" align="center">Exp (&#x3b2;)</th>
<th valign="middle" align="center">&#x3b2;</th>
<th valign="middle" align="center">95%CI</th>
<th valign="middle" align="center">Exp (&#x3b2;)</th>
<th valign="middle" align="center">&#x3b2;</th>
<th valign="middle" align="center">95%CI</th>
<th valign="middle" align="center">Exp (&#x3b2;)</th>
<th valign="middle" align="center">&#x3b2;</th>
<th valign="middle" align="center">95%CI</th>
<th valign="middle" align="center">Exp (&#x3b2;)</th>
<th valign="middle" align="center">&#x3b2;</th>
<th valign="middle" align="center">95%CI</th>
<th valign="middle" align="center">Exp (&#x3b2;)</th>
<th valign="middle" align="center">&#x3b2;</th>
<th valign="middle" align="center">95%CI</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="16" align="left">Continuous analysis</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron</td>
<td valign="middle" align="center">0.859</td>
<td valign="middle" align="center">-0.066</td>
<td valign="middle" align="center">-0.201;0.070</td>
<td valign="middle" align="center">0.964</td>
<td valign="middle" align="center">-0.016</td>
<td valign="middle" align="center">-0.073;0.041</td>
<td valign="middle" align="center">0.631</td>
<td valign="middle" align="center">-0.200</td>
<td valign="middle" align="center">-0.398;0.000</td>
<td valign="middle" align="center">0.735</td>
<td valign="middle" align="center">-0.134</td>
<td valign="middle" align="center">-0.341;0.074</td>
<td valign="middle" align="center">0.642</td>
<td valign="middle" align="center">-0.192</td>
<td valign="middle" align="center">-0.394;0.011</td>
</tr>
<tr>
<th valign="middle" colspan="16" align="left">Analysis by quartiles</th>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Q1 (0.12-0.59 &#x3bc;g/mL)</td>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">1</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center"/>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Q2 (0.59-0.81 &#x3bc;g/mL)</td>
<td valign="middle" align="center">0.918</td>
<td valign="middle" align="center">-0.037</td>
<td valign="middle" align="center">-0.136;0.062</td>
<td valign="middle" align="center">0.969</td>
<td valign="middle" align="center">-0.014</td>
<td valign="middle" align="center">-0.055;0.028</td>
<td valign="middle" align="center">0.804</td>
<td valign="middle" align="center">-0.095</td>
<td valign="middle" align="center">-0.246;0.054</td>
<td valign="middle" align="center">0.718</td>
<td valign="middle" align="center">-0.144</td>
<td valign="middle" align="center">-0.300;0.011</td>
<td valign="middle" align="center">0.742</td>
<td valign="middle" align="center">-0.130</td>
<td valign="middle" align="center">-0.282;0.021</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Q3 (0.81-1.06 &#x3bc;g/mL)</td>
<td valign="middle" align="center">1.050</td>
<td valign="middle" align="center">0.021</td>
<td valign="middle" align="center">-0.093;0.136</td>
<td valign="middle" align="center">0.984</td>
<td valign="middle" align="center">-0.007</td>
<td valign="middle" align="center">-0.055;0.041</td>
<td valign="middle" align="center">0.672</td>
<td valign="middle" align="center">-0.172</td>
<td valign="middle" align="center">-0.351;0.005</td>
<td valign="middle" align="center">0.666</td>
<td valign="middle" align="center">-0.177</td>
<td valign="middle" align="center">-0.361;0.008</td>
<td valign="middle" align="center">0.616</td>
<td valign="middle" align="center">-0.210</td>
<td valign="middle" align="center">-0.389;-0.030</td>
</tr>
<tr>
<td valign="middle" align="left">&#x2003;Q4 (1.06-1.91 &#x3bc;g/mL)</td>
<td valign="middle" align="center">0.910</td>
<td valign="middle" align="center">-0.041</td>
<td valign="middle" align="center">-0.161;0.079</td>
<td valign="middle" align="center">0.975</td>
<td valign="middle" align="center">-0.011</td>
<td valign="middle" align="center">-0.061;0.040</td>
<td valign="middle" align="center">0.661</td>
<td valign="middle" align="center">-0.180</td>
<td valign="middle" align="center">-0.356;-0.003</td>
<td valign="middle" align="center">0.663</td>
<td valign="middle" align="center">-0.178</td>
<td valign="middle" align="center">-0.361;0.005</td>
<td valign="middle" align="center">0.625</td>
<td valign="middle" align="center">-0.204</td>
<td valign="middle" align="center">-0.382;-0.025</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Results were derived from linear mixed-effect models, using a random intercept for individuals and antibody or NAb levels as outcomes; model were adjusted for antibody level at baseline, vaccine type and number of vaccine doses received, time point of study visit, time of the day of study visit, re-exposure at study visit, CRP, AGP, RBP, age, sex, smoking status. Complete results are presented in <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Tables S3</bold></xref> and <xref ref-type="supplementary-material" rid="SM1"><bold>S4</bold></xref>.</p></fn>
<fn>
<p>Coefficients &#x3b2; are on the log10 scale; exp(&#x3b2;), i.e. 10<sup>&#x3b2;</sup>, represents the multiplicative factor changes in antibody or NAb levels associated with a 1 &#x3bc;g/mL increase in plasma iron levels in continuous analyses or compared to plasma iron Q1 in categorical analyses.</p></fn>
<fn>
<p>Models were based on a study sample of n=553 for Anti-S IgA, n=553 for Anti-S IgG, n=209 for Anti-Ancestral NAb, n=209 for Anti-Delta NAb, n=209 for Anti-Omicron NAb.</p></fn>
<fn>
<p>AGP, alpha(1)-acid glycoprotein; CI, confidence intervals; CRP, c-reactive protein; NAb, neutralizing antibodies; Q, quartile; RBP, retinol binding protein.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Analyses of plasma iron were generally less consistent across different markers of immunity (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4</bold></xref>). No evidence for an association between plasma iron concentrations and antibody or NAb levels was observed when plasma iron was included as continuous variable in the models. When investigating quartiles of plasma iron levels, individuals in the highest quartile of plasma iron had a 33.9% lower antibody response for Anti-Ancestral NAb and a 37.5% lower antibody response for Anti-Omicron NAb levels compared to those in the lowest quartile. We found no evidence that quartiles of plasma iron levels were associated with Anti-S IgA antibodies, Anti-S IgG antibodies, and Anti-Delta NAb.</p>
<p>Results of covariates in all models showed a high level of consistency across iron parameters and markers of immunity (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Tables S1-S4</bold></xref>). As expected, baseline antibody concentration was positively associated with the immune response. In addition, re-exposure to SARS-CoV-2, either by infection or subsequent vaccination, was associated with a markedly higher immune response. Receiving two doses of the Moderna mRNA-1273 vaccine was associated with a higher immune response, while receiving the Johnson &amp; Johnson JNJ-78436735 vaccine was associated with a lower immune response compared to receiving two doses of either mRNA vaccine. Finally, the immune response following vaccination was decreased with increasing age and was lower in males compared to females.</p>
<p>We also explored the association of antibody and NAb levels with plasma ferritin and plasma iron at single time points of study follow-up. Results of models including plasma ferritin are shown in <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S5</bold></xref>. Consistent with the results of the longitudinal analyses, significant positive associations were observed for Anti-S IgG as well as for NAb against the Ancestral, Delta and Omicron viral variants, whereas no evidence for an association with plasma ferritin levels was observed for Anti-S IgA. For Anti-S IgG antibodies, we observed a 9.0% increase in antibody levels for every 50 &#x3bc;g/L increase in plasma ferritin concentration at 4 weeks, but no evidence for an association at 6 weeks, i.e., after participants received the second vaccine dose. Evidence for positive associations was again observed at 3 months and 6 months, where we observed a 3.8% and 5.3% increase in Anti-S IgG antibody levels for every 50 &#x3bc;g/L increase in plasma ferritin, respectively. In models investigating NAb, positive associations were observed at 3 months (19.0% increase for Anti-Ancestral, 28.6% for Anti-Delta and 28.7% for Anti-Omicron NAb for every 50 &#x3bc;g/L increase in plasma ferritin concentration). For plasma iron, no relevant trends were observed in analyses at individual time points of study follow-up (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S6</bold></xref>). Generally, we found no evidence for associations between plasma iron concentrations and immunity markers, with a few exceptions.</p>
<p>In general, sensitivity analyses including comorbidity as an adjustment factor in the models, excluding participants with inflammation, not adjusting the models for CRP and AGP, and adjusting the analyses of NAb for seropositivity at baseline and knowledge of a prior infection instead of baseline Anti-S IgG level did not improve the model fit and did not meaningfully change the study results (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Tables S7-S10</bold></xref>). Not adjusting the models for CRP and AGP and adjusting the NAb analyses for seropositivity at baseline and knowledge of a prior infection tended to move the plasma iron results slightly away from the null (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Tables S9-S10</bold></xref>).</p>
<p>Next, we estimated the half-life of the different markers of immune response based on linear decay models. The temporal development of different immunity markers by plasma ferritin and plasma iron quartiles is presented in <xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>. Mean antibody levels at 6 months were high in the overall study population as well as across all plasma ferritin and plasma iron quartiles (<xref ref-type="fig" rid="f1"><bold>Figures&#xa0;1A&#x2013;D</bold></xref>, <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S11</bold></xref>). Mean NAb levels at 6 months were also high against the Ancestral, but lower against the Delta and Omicron viral variants (<xref ref-type="fig" rid="f1"><bold>Figures&#xa0;1E&#x2013;J</bold></xref>, <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S11</bold></xref>). It should be noted that the sample size for analyses of the Omicron viral variant was limited and the half-life of Anti-Omicron NAb could not be estimated.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Temporal development of different immunity markers by plasma ferritin and plasma iron quartiles. <bold>(A)</bold> Anti-S IgA antibody levels by plasma ferritin quartiles (n=550). <bold>(B)</bold> Anti-S IgA antibody levels by plasma iron quartiles (n=540). <bold>(C)</bold> Anti-S IgG antibody levels by plasma ferritin quartiles (n=570). <bold>(D)</bold> Anti-S IgG antibody levels by plasma iron quartiles (n=560). <bold>(E)</bold> Anti-Ancestral NAb levels by plasma ferritin quartiles (n=184). <bold>(F)</bold> Anti-Ancestral NAb levels by plasma iron quartiles (n=181). <bold>(G)</bold> Anti-Delta NAb levels by plasma ferritin quartiles (n=138). <bold>(H)</bold> Anti-Delta NAb levels by plasma iron quartiles (n=136). <bold>(I)</bold> Anti-Omicron NAb levels by plasma ferritin quartiles (n=75). <bold>(J)</bold> Anti-Omicron NAb levels by plasma iron quartiles (n=73). Antibody level is expressed as geometric mean (95% CI) MFI ratio for Anti-S IgA and Anti-S IgG antibodies, and as geometric mean (95% CI) IC<sub>50</sub> for Anti-Ancestral, Anti-Delta, and Anti-Omicron NAb. Time points in which participants reported a re-exposure or antibody levels increased (post-vaccination or potential undiagnosed SARS-CoV-2 infection) were excluded. CI, confidence interval; IC<sub>50</sub>, half maximal inhibitory concentration serum dilution; NAb, neutralizing antibodies; Q, quartiles.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-17-1764884-g001.tif">
<alt-text content-type="machine-generated">Ten line charts display longitudinal immune response data by plasmaferritin and plasma iron quartiles, with panels A, C, E, G, and I for plasma ferritin and B, D, F, H, and J for plasma iron; outcomes are anti-S IgA MFI ratio (A, B), anti-S IgG MFI ratio (C, D), anti-Ancestral neutralizing antibody IC50 (E,F), anti-Delta neutralizing antibody IC50 (G, H), and anti-Omicron neutralizing antibody IC50 (I, J). Outcomes are presented as geometric means and ninety-five percentconfidence intervals. Time points include baseline, week four, week six, month three, and month six for antibodies, and week four, monththree, and month six for neutralizing antibodies.</alt-text>
</graphic></fig>
<p>The estimated half-lives in days by plasma ferritin levels are shown in <xref ref-type="table" rid="T5"><bold>Table&#xa0;5</bold></xref>. Generally, Anti-S IgG antibodies had a longer half-life (ranging from 110 to 150 days) than Anti-S IgA antibodies (ranging from 58 to 64 days) as well as Anti-Ancestral and Anti-Delta NAb (ranging from 55 to 85 days). For Anti-S IgG antibodies, the estimated decay time decreased with increasing plasma ferritin levels prior to vaccination. Compared to participants in the first (lowest) quartile of plasma ferritin levels (152.1 days, 95% CI 131.6,172.7), the half-life was shorter in participants in the third quartile (121.4 days, 95% CI 108.5,134.3, p-value=0.009) and fourth quartile (109.8 days, 95% CI 99.1,120.3, p-value&lt;0.001) of plasma ferritin concentrations. This might seem counterintuitive, as a longer half-life is desirable and in previous analyses, higher plasma ferritin concentration was associated with higher Anti-S IgG antibody levels. In contrast, for Anti-Ancestral NAb, participants in the third quartile of plasma ferritin levels (81.6 days, 95% CI 61.7,101.5, p-value=0.002) showed a longer half-life compared to participants in the first quartile of plasma ferritin levels (54.6 days, 95% CI 47.4,61.8; <xref ref-type="table" rid="T5"><bold>Table&#xa0;5</bold></xref>).</p>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Decay estimation of different markers of immune response by plasma ferritin level prior to vaccination.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Immunity markers</th>
<th valign="middle" colspan="2" align="center">Unadjusted half-life</th>
<th valign="middle" colspan="2" align="center">Adjusted half-life</th>
</tr>
<tr>
<th valign="middle" align="center"/>
<th valign="middle" align="center">Days (95% CI)</th>
<th valign="middle" align="center">P-value</th>
<th valign="middle" align="center">Days (95% CI)</th>
<th valign="middle" align="center">P-value</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="5" align="left">Anti-S IgA</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q1 (4.3-62.1 &#x3bc;g/L)</td>
<td valign="middle" align="center">63.9 (57.1;70.6)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">62.8 (56.6;68.9)</td>
<td valign="middle" align="center">Ref</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q2 (62.2-96.3 &#x3bc;g/L)</td>
<td valign="middle" align="center">62.0 (55.3;68.7)</td>
<td valign="middle" align="center">0.705</td>
<td valign="middle" align="center">61.5 (55.4;67.6)</td>
<td valign="middle" align="center">0.776</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q3 (96.4-140.9 &#x3bc;g/L)</td>
<td valign="middle" align="center">57.9 (52.1;63.8)</td>
<td valign="middle" align="center">0.194</td>
<td valign="middle" align="center">58.4 (52.9;64.0)</td>
<td valign="middle" align="center">0.301</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q4 (141.0-250.0 &#x3bc;g/L)</td>
<td valign="middle" align="center">60.5 (53.9;67.0)</td>
<td valign="middle" align="center">0.483</td>
<td valign="middle" align="center">63.2 (56.6;69.8)</td>
<td valign="middle" align="center">0.928</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Anti-S IgG</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q1 (4.3-62.1 &#x3bc;g/L)</td>
<td valign="middle" align="center">148.8 (125.8;171.8)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">152.1 (131.6;172.7)</td>
<td valign="middle" align="center">Ref</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q2 (62.2-96.3 &#x3bc;g/L)</td>
<td valign="middle" align="center">147.3 (127.0;167.6)</td>
<td valign="middle" align="center">0.924</td>
<td valign="middle" align="center">147.5 (129.9;165.1)</td>
<td valign="middle" align="center">0.734</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q3 (96.4-140.9 &#x3bc;g/L)</td>
<td valign="middle" align="center">117.2 (103.2;131.2)</td>
<td valign="middle" align="center">0.015</td>
<td valign="middle" align="center">121.4 (108.5;134.3)</td>
<td valign="middle" align="center">0.009</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q4 (141.0-250.0 &#x3bc;g/L)</td>
<td valign="middle" align="center">110.7 (98.4;122.9)</td>
<td valign="middle" align="center">0.002</td>
<td valign="middle" align="center">109.8 (99.4;120.3)</td>
<td valign="middle" align="center">&lt;0.001</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Anti-Ancestral NAb</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q1 (4.3-62.1 &#x3bc;g/L)</td>
<td valign="middle" align="center">56.5 (47.2;65.8)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">54.6 (47.4;61.8)</td>
<td valign="middle" align="center">Ref</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q2 (62.2-96.3 &#x3bc;g/L)</td>
<td valign="middle" align="center">69.8 (55.1;84.5)</td>
<td valign="middle" align="center">0.118</td>
<td valign="middle" align="center">66.6 (55.5;77.7)</td>
<td valign="middle" align="center">0.061</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q3 (96.4-140.9 &#x3bc;g/L)</td>
<td valign="middle" align="center">84.6 (58.6;110.7)</td>
<td valign="middle" align="center">0.015</td>
<td valign="middle" align="center">81.6 (61.7;101.5)</td>
<td valign="middle" align="center">0.002</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q4 (141.0-250.0 &#x3bc;g/L)</td>
<td valign="middle" align="center">70.1 (47.3;92.9)</td>
<td valign="middle" align="center">0.222</td>
<td valign="middle" align="center">69.3 (51.1;87.5)</td>
<td valign="middle" align="center">0.089</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Anti-Delta NAb</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q1 (4.3-62.1 &#x3bc;g/L)</td>
<td valign="middle" align="center">59.7 (48.2;71.3)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">57.0 (48.2;65.7)</td>
<td valign="middle" align="center">Ref</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q2 (62.2-96.3 &#x3bc;g/L)</td>
<td valign="middle" align="center">73.2 (52.8;93.7)</td>
<td valign="middle" align="center">0.229</td>
<td valign="middle" align="center">66.5 (52.8;80.3)</td>
<td valign="middle" align="center">0.226</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q3 (96.4-140.9 &#x3bc;g/L)</td>
<td valign="middle" align="center">70.4 (49.1;91.6)</td>
<td valign="middle" align="center">0.359</td>
<td valign="middle" align="center">66.7 (51.2;82.2)</td>
<td valign="middle" align="center">0.252</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin Q4 (141.0-250.0 &#x3bc;g/L)</td>
<td valign="middle" align="center">63.4 (42.6;84.2)</td>
<td valign="middle" align="center">0.756</td>
<td valign="middle" align="center">60.9 (45.8;76.0)</td>
<td valign="middle" align="center">0.647</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Anti-Omicron NAb</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma ferritin</td>
<td valign="middle" align="center">Not estimable</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">Not estimable</td>
<td valign="middle" align="center"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Results were derived from linear mixed-effect models, using a random intercept for individuals, antibody or NAb levels as outcomes, and including an interaction term between days since maximum antibody concentration and plasma ferritin quartiles.</p></fn>
<fn>
<p>Estimated half-life was calculated using the formula log(0.5)/&#x3b2;, where &#x3b2; is the model-derived estimate of the interaction term between days since maximum antibody concentration and plasma ferritin quartiles; 95% CI were calculated using the delta method.</p></fn>
<fn>
<p>Adjusted half-life was derived from models adjusted for maximum antibody concentration, vaccine type and number of vaccine doses received, CRP, AGP, RBP, age, sex, smoking status.</p></fn>
<fn>
<p>Models were based on a study sample of n=550 for Anti-S IgA, n=570 for Anti-S IgG, n=184 for Anti-Ancestral NAb, n=138 for Anti-Delta NAb.</p></fn>
<fn>
<p>AGP, alpha(1)-acid glycoprotein; CI, confidence intervals; CRP, c-reactive protein; NAb, neutralizing antibodies; Q: quartile; RBP, retinol binding protein.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>Analogous results for plasma iron analyses are presented in <xref ref-type="table" rid="T6"><bold>Table&#xa0;6</bold></xref>. Again, Anti-S IgG antibodies had a longer half-life (ranging from 122 to 143 days) compared to Anti-S IgA antibodies (ranging from 60 to 65 days) as well as Anti-Ancestral and Anti-Delta NAb (ranging from 55 to 85 days). However, no clear trend was observed in analyses of plasma iron and generally, no differences were observed in the estimated half-life by plasma iron quartiles (<xref ref-type="table" rid="T6"><bold>Table&#xa0;6</bold></xref>).</p>
<table-wrap id="T6" position="float">
<label>Table&#xa0;6</label>
<caption>
<p>Decay estimation of different markers of immune response by plasma iron level prior to vaccination.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Immunity markers</th>
<th valign="middle" colspan="2" align="center">Unadjusted half-life</th>
<th valign="middle" colspan="2" align="center">Adjusted half-life</th>
</tr>
<tr>
<th valign="middle" align="left"/>
<th valign="middle" align="center">Days (95% CI)</th>
<th valign="middle" align="center">p-value</th>
<th valign="middle" align="center">Days (95% CI)</th>
<th valign="middle" align="center">p-value</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="middle" colspan="5" align="left">Anti-S IgA</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q1 (0.12-0.59 &#x3bc;g/mL)</td>
<td valign="middle" align="center">60.1 (53.8;66.5)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">60.6 (54.7;66.6)</td>
<td valign="middle" align="center">Ref</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q2 (0.59-0.81 &#x3bc;g/mL)</td>
<td valign="middle" align="center">60.8 (54.2;67.4)</td>
<td valign="middle" align="center">0.891</td>
<td valign="middle" align="center">60.7 (54.6;66.8)</td>
<td valign="middle" align="center">0.980</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q3 (0.81-1.06 &#x3bc;g/mL)</td>
<td valign="middle" align="center">63.6 (56.6;70.6)</td>
<td valign="middle" align="center">0.470</td>
<td valign="middle" align="center">65.3 (58.5;72.2)</td>
<td valign="middle" align="center">0.303</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q4 (1.06-1.91 &#x3bc;g/mL)</td>
<td valign="middle" align="center">60.1 (53.7;66.5)</td>
<td valign="middle" align="center">0.990</td>
<td valign="middle" align="center">59.5 (53.7;65.4)</td>
<td valign="middle" align="center">0.803</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Anti-S IgG</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q1 (0.12-0.59 &#x3bc;g/mL)</td>
<td valign="middle" align="center">133.4 (116.0;150.7)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">134.2 (119.1;149.3)</td>
<td valign="middle" align="center">Ref</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q2 (0.59-0.81 &#x3bc;g/mL)</td>
<td valign="middle" align="center">122.1 (107.2;137.0)</td>
<td valign="middle" align="center">0.333</td>
<td valign="middle" align="center">124.5 (111.1;137.9)</td>
<td valign="middle" align="center">0.340</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q3 (0.81-1.06 &#x3bc;g/mL)</td>
<td valign="middle" align="center">139.2 (118.8;159.6)</td>
<td valign="middle" align="center">0.668</td>
<td valign="middle" align="center">142.7 (124.2;161.3)</td>
<td valign="middle" align="center">0.478</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q4 (1.06-1.91 &#x3bc;g/mL)</td>
<td valign="middle" align="center">125.2 (109.2;141.2)</td>
<td valign="middle" align="center">0.499</td>
<td valign="middle" align="center">126.6 (112.4;140.7)</td>
<td valign="middle" align="center">0.465</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Anti-Ancestral NAb</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q1 (0.12-0.59 &#x3bc;g/mL)</td>
<td valign="middle" align="center">67.7 (51.9;83.4)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">62.8 (51.7;74.0)</td>
<td valign="middle" align="center">Ref</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q2 (0.59-0.81 &#x3bc;g/mL)</td>
<td valign="middle" align="center">57.9 (46.2;69.6)</td>
<td valign="middle" align="center">0.321</td>
<td valign="middle" align="center">56.8 (47.6;65.9)</td>
<td valign="middle" align="center">0.399</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q3 (0.81-1.06 &#x3bc;g/mL)</td>
<td valign="middle" align="center">78.8 (56.9;100.6)</td>
<td valign="middle" align="center">0.409</td>
<td valign="middle" align="center">77.2 (60.0;94.5)</td>
<td valign="middle" align="center">0.148</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q4 (1.06-1.91 &#x3bc;g/mL)</td>
<td valign="middle" align="center">68.1 (52.9;83.4)</td>
<td valign="middle" align="center">0.966</td>
<td valign="middle" align="center">65.8 (53.9;77.6)</td>
<td valign="middle" align="center">0.723</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Anti-Delta NAb</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q1 (0.12-0.59 &#x3bc;g/mL)</td>
<td valign="middle" align="center">74.7 (55.0;94.3)</td>
<td valign="middle" align="center">Ref</td>
<td valign="middle" align="center">70.5 (56.0;85.0)</td>
<td valign="middle" align="center">Ref</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q2 (0.59-0.81 &#x3bc;g/mL)</td>
<td valign="middle" align="center">54.3 (42.2;66.4)</td>
<td valign="middle" align="center">0.072</td>
<td valign="middle" align="center">51.7 (42.8;60.5)</td>
<td valign="middle" align="center">0.021</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q3 (0.81-1.06 &#x3bc;g/mL)</td>
<td valign="middle" align="center">66.9 (48.0;85.8)</td>
<td valign="middle" align="center">0.583</td>
<td valign="middle" align="center">63.3 (49.3;77.2)</td>
<td valign="middle" align="center">0.479</td>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron Q4 (1.06-1.91 &#x3bc;g/mL)</td>
<td valign="middle" align="center">68.3 (51.3;85.3)</td>
<td valign="middle" align="center">0.631</td>
<td valign="middle" align="center">65.5 (52.7;78.2)</td>
<td valign="middle" align="center">0.607</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left">Anti-Omicron NAb</th>
</tr>
<tr>
<td valign="middle" align="left">Plasma iron</td>
<td valign="middle" align="center">Not estimable</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">Not estimable</td>
<td valign="middle" align="center"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Results were derived from linear mixed-effect models, using a random intercept for individuals, antibody or NAb levels as outcomes, and including an interaction term between days since maximum antibody concentration and plasma iron quartiles.</p></fn>
<fn>
<p>Estimated half-life was calculated using the formula log(0.5)/&#x3b2;, where &#x3b2; is the model-derived estimate of the interaction term between days since maximum antibody concentration and plasma iron quartiles; 95% CI were calculated using the delta method.</p></fn>
<fn>
<p>Adjusted half-life was derived from models adjusted for maximum antibody concentration, vaccine type and number of vaccine doses received, time of the day of study visit, CRP, AGP, RBP, age, sex, smoking status.</p></fn>
<fn>
<p>Models were based on a study sample of n=540 for Anti-S IgA, n=560 for Anti-S IgG, n=181 for Anti-Ancestral NAb, n=136 for Anti-Delta NAb.</p></fn>
<fn>
<p>AGP, alpha(1)-acid glycoprotein; CI, confidence intervals; CRP: c-reactive protein; NAb, neutralizing antibodies; Q, quartiles; RBP, retinol binding protein.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>In this iron-replete study population, plasma ferritin concentration at the time of vaccination was positively associated with Anti-S IgG antibodies, and Anti-Ancestral, Anti-Delta, and Anti-Omicron NAb over 6 months. Plasma iron results were less consistent and generally, we found no evidence for an association between plasma iron levels and immunity markers. Higher Anti-S IgG antibody levels from 6 weeks to 3 months resulted in shorter half-lives of these antibodies in participants in the third and fourth quartiles of plasma ferritin concentrations compared to those in the first quartile. Despite this, Anti-S IgG concentrations at 6 months remained high across all quartile groups.</p>
<p>Ferritin is a well-established positive acute-phase reactant. Therefore, we adjusted all our models for markers of inflammation. In addition, we conducted a sensitivity analysis including only participants without inflammation. In this sensitivity analysis, the associations between plasma ferritin and immunity markers were very similar to those observed in the main analyses (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S8</bold></xref>). However, given the observational nature of this study, residual confounding cannot be entirely excluded, and our findings have to be interpreted with caution.</p>
<p>For every 50 &#x3bc;g/L increase in plasma ferritin concentration, we found a 5% increase in Anti-S IgG antibodies and an increase between 14-20% in NAb against the Ancestral, Delta and Omicron viral variants over 6 months. Similarly, individuals in the highest quartile of plasma ferritin showed a 15% increase in Anti-S IgG antibodies and an increase between 47-82% in NAb compared to individuals in the lowest quartile (<xref ref-type="table" rid="T3"><bold>Table&#xa0;3</bold></xref>). Despite the significant associations, differences in antibody responses by iron status were small in magnitude and minor compared to other established determinants of vaccination efficacy, such as vaccine type and baseline antibody levels (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Tables S1-S4</bold></xref>). Mean antibody and NAb levels at 6 months were generally high irrespective of iron status (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>, <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S11</bold></xref>). In addition, seropositivity (defined as MFI ratio &gt; 6.5 for IgA and MFI ratio &gt; 6.0 for IgG antibodies) and neutralizing capacity (defined as serum dilution IC<sub>50</sub> &gt;50 for Anti-Ancestral, Anti-Delta, and Anti-Omicron NAb) at 6 months were generally consistent across quartiles of iron status (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S12</bold></xref>). This indicates that the clinical implications of our results may be limited.</p>
<p>As the prevalence of iron deficiency in this study was low (4.5% in the overall study population and 17.5% in women of reproductive age), our finding of a positive association of plasma ferritin with most of the considered markers of immunity is somewhat surprising. The analyses by plasma ferritin quartiles indicated higher Anti-S IgG antibody and NAb levels in the subgroup with highest plasma ferritin concentrations (141.0-250.0 &#xb5;g/L) compared to participants with the lowest plasma ferritin concentrations (4.3-62.1 &#xb5;g/L). This result could be due to a suboptimal antibody response in the reference group, showing significant differences only in comparison with the group most different from the reference, i.e. the highest quartile of the plasma ferritin distribution. A further possible explanation is a positive effect of high plasma ferritin in this population on the antibody response to vaccination. A recent comprehensive analysis of drivers of post-acute sequelae of SARS-CoV-2 (or &#x201c;long COVID&#x201d;) suggested that delayed resolution of inflammation-associated hypoferremia best discriminated patients reporting persistent symptoms (<xref ref-type="bibr" rid="B28">28</xref>). Thus, abnormal iron distribution and functional iron deficiency at time of infection appear to be important risk factors for an inappropriate immune response to SARS-CoV-2. These results are broadly consistent with our observation of an association between high plasma ferritin and high antibody responses to SARS-CoV-2 vaccination. In the IRONMAN prospective randomized trial, conducted at the height of the COVID-19 pandemic and including subjects with heart failure and iron deficiency (defined as transferrin saturation &lt;20% or serum ferritin &lt;100 &#xb5;g/L), treatment with intravenous iron reduced the risk of hospitalization for infection (hazard ratio 0.76, 95% CI 0.49-0.98), and a secondary analysis suggested that the effect was particularly pronounced in patients with hypoferremia (<xref ref-type="bibr" rid="B29">29</xref>). This finding is consistent with the observation that iron overload in &#x3b2;-thalassemia patients infected with SARS-CoV-2 was protective against in-hospital complications and all-cause mortality compared to matched controls (<xref ref-type="bibr" rid="B30">30</xref>). In another study, high ferritin (&gt;600 ng/mL) was found to be an independent predictor of antibody levels after administration of SARS-CoV-2 vaccines in hemodialysis patients (<xref ref-type="bibr" rid="B31">31</xref>). These studies support the concept that the absence of functional iron deficiency at the time of vaccination (irrespective of plasma ferritin levels) results in a stronger SARS-CoV-2 immune response (<xref ref-type="bibr" rid="B28">28</xref>) and call for further studies on the interaction between immunity and iron status in vulnerable population groups.</p>
<p>The hepcidin induced hypoferremia of inflammation has an innate short term protective role reducing the amount of systemic iron in circulation and limiting pathogen proliferation (<xref ref-type="bibr" rid="B32">32</xref>). While plasma iron was not associated with antibody response in the continuous analyses of our study, being in the highest quartile of plasma iron was associated with lower Anti-Ancestral NAb and Anti-Omicron NAb concentrations. A possible explanation for this effect is that subjects with higher plasma iron levels tended to have higher antibody levels prior to vaccination, resulting in a more blunted immune response to vaccines, an effect that has also been described for influenza vaccinations (<xref ref-type="bibr" rid="B27">27</xref>). This explanation is supported by a substantial shift away from the null in the association between plasma iron and NAb when the models were not adjusted for baseline antibody levels (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S13</bold></xref>).</p>
<p>In the current study, the estimated decay time for Anti-S IgG antibodies decreased with increasing plasma ferritin levels. This appears to be in contrast with the effect detected in linear mixed-effect models investigating the longitudinal association between Anti-S IgG antibody levels and plasma ferritin concentrations, where we observed a significantly higher immune response in individuals with higher plasma ferritin levels. The shorter half-life of Anti-S IgG antibodies in the higher plasma ferritin quartiles likely resulted from higher maximum antibody concentrations in these individuals, leading to a more rapid decline in Anti-S IgG antibody concentrations over time. Despite this, mean Anti-S IgG concentration at 6 months was high, indicating a robust immune response (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Table S11</bold></xref>). A somewhat opposite effect was observed for Anti-Ancestral NAb, where higher plasma ferritin levels tended to be associated with a longer NAb half-life. The reason for this discrepancy is not immediately clear, but it has been suggested that different B cell subtypes (long-lived plasma cells <italic>vs</italic> short-lived plasma blasts) may react differently to iron availability (<xref ref-type="bibr" rid="B33">33</xref>).</p>
<p>To our knowledge only a few studies have investigated the influence of iron status on the immune response following SARS-CoV-2 vaccination, with most studies only focusing on the short-term effectiveness of vaccination. Faizo et&#xa0;al. (<xref ref-type="bibr" rid="B14">14</xref>) observed no differences in antibody levels and neutralizing capacity when investigating the SARS-CoV-2 vaccine-induced immunity in iron-deficient <italic>vs</italic>. iron-replete controls. However, the assessment of iron status after rather than at the time of vaccination, the difference in time since vaccination, the limited sample size, and the sex imbalance between the study groups might have influenced the results of this study (<xref ref-type="bibr" rid="B14">14</xref>). Furthermore, in a randomized controlled trial providing ferric carboxymaltose to kidney transplant recipients with iron deficiency, no differences in humoral and cellular immune response following SARS-CoV-2 vaccination were observed between study groups after vaccination (<xref ref-type="bibr" rid="B34">34</xref>). When comparing iron-deficient and iron-replete individuals, Tene et&#xa0;al. (<xref ref-type="bibr" rid="B35">35</xref>) found a similar SARS-CoV-2 vaccine effectiveness and comparable hospitalization and mortality rates between study groups at 3 weeks after the second vaccination. Interestingly, although without evidence for statistically significant differences, this study also found that the one-dose vaccine effectiveness was numerically lower in individuals with iron deficiency compared to individuals without iron deficiency. Similar results were observed in an intervention study, where anemic Kenyan women who received intravenous iron before vaccination with the ChAdOx vaccine (Oxford-AstraZeneca COVID-19) showed higher IgG antibodies after the first vaccination, compared to those who did not received iron before vaccination, but no difference was observed after the second vaccination (unpublished data (<xref ref-type="bibr" rid="B33">33</xref>)). This is consistent with our study, as we found positive associations between plasma ferritin concentrations at time of vaccination and Anti-S IgG antibodies at week 4, i.e. after participants received the first vaccine dose, but not at week 6, i.e. after participants received the second vaccine dose. Nevertheless, evidence for positive associations was again observed at 3 months and 6 months in analyses including plasma ferritin as continuous variable.</p>
<p>In our study, we observed a clear antibody and NAb response shortly after SARS-CoV-2 vaccination irrespective of iron status (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>). This is in line with previous studies reporting a high two-dose effectiveness of SARS-CoV-2 in both iron-replete and iron-deficient individuals (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B35">35</xref>) as well as with previous efficacy trials (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>). These results may indicate that a timely use of SARS-CoV-2 vaccines in iron-deficient individuals might be more advantageous than delaying vaccination to correct iron deficiency, which contrasts the recommendation issued by the European Hematology Association. Although our study was not suited to investigate effects among iron-deficient individuals, the weaker immune response observed among individuals with low iron levels prior to vaccination with a SARS-CoV-2 mRNA vaccine, which is known to induce a strong antibody response, suggests that the impact of iron levels on the efficacy of other vaccines requires further investigation.</p>
<p>This study used data from a population-based representative cohort study, timely established after the beginning of the administration of SARS-CoV-2 vaccines in Switzerland. Analyses included data collected from the time of vaccination until 6 months post vaccination. We performed a comprehensive analysis considering different markers of immune response, and plasma ferritin and plasma iron as indicators of iron status. Iron parameters were measured in the baseline samples, which were collected immediately before receiving the first vaccine dose, reflecting iron status at time of vaccination. Additionally, Anti-S IgA and Anti-S IgG antibodies were also measured in the baseline samples, providing information on antibody levels prior to vaccination. In all analyses, results of covariates showed a high level of consistency across iron parameters and markers of immunity and were in agreement with predictors of SARS-CoV-2 immune response identified in previously published studies. However, this study also has some limitations. First, iron parameters were measured in plasma samples and concentrations of plasma iron could have been affected by hemoglobin iron potentially present in the samples as a consequence of hemolysis. However, we corrected plasma iron concentrations for hemoglobin iron by assessing the degree of hemolysis and comparing this to a calibration curve prepared from plasma and hemolyzed whole blood (<xref ref-type="bibr" rid="B22">22</xref>). In addition, since the timing of blood collection was not standardized in the Zurich SARS-CoV-2 Vaccine Cohort Study, variability in plasma iron concentration related to the circadian variation cannot be excluded. However, we adjusted all analyses of plasma iron for the time of the day of study visit. Second, only a few participants were iron-deficient, precluding the possibility to compare iron-deficient and iron-replete individuals in this study. Therefore, study findings cannot be reliably generalized to iron-deficient populations. Nevertheless, we divided participants into groups based on plasma ferritin and plasma iron quartiles, which enabled us to conduct analyses comparing individuals with a relatively low iron status, but with a sufficient number of participants. Third, as an acute phase protein, it has been speculated whether ferritin could be a trigger for further propagation of an inflammatory cascade rather than a sole marker of inflammation (<xref ref-type="bibr" rid="B38">38</xref>). While the former cannot be excluded in this study, our participants were in large part naive to SARS-CoV-2 before vaccination. Fourth, the measurement of antibody responses in this study relied on a Luminex-based assay and test accuracy might have influenced the assessment of antibody levels. However, an extensive validation of the Luminex assay was performed prior to the start of the study, resulting into high sensitivity and specificity and showing high levels of agreement with results of two commercially available assays (<xref ref-type="bibr" rid="B23">23</xref>). Fifth, neutralizing activity was quantified indirectly with a surrogate assay by measuring the competitive inhibition of the SARS-CoV-2 S protein binding to the Angiotensin Converting Enzyme 2 (ACE2) receptor. Nevertheless, validation of this assay resulted in very high sensitivity compared to assays of live viruses. In addition, this allowed the simultaneous assessment of Anti-Ancestral, Anti-Delta, and Anti-Omicron NAb (<xref ref-type="bibr" rid="B23">23</xref>). Sixth, NAb were measured only in a subset of study participants, leading to a relatively low sample size in these analyses, particularly for the Omicron viral variant in analyses of the decay time. Seventh, as antibody and NAb concentrations were measured at pre-defined time points of study follow-up, the full kinetic profile of the immune response was not available. Therefore, the participants&#x2019; true maximum antibody or NAb concentration may not have been captured by the study measures, which could have influenced the results of the decay analysis. Finally, cellular immune response to vaccination was not investigated in this study.</p>
<p>To conclude, in this predominantly iron-replete cohort with ferritin concentrations within the normal physiological range, higher plasma ferritin at the time of vaccination was associated with a more marked vaccination-induced immune response to SARS-CoV-2 over 6 months. Furthermore, shorter half-lives of Anti-S IgG antibodies were observed in participants in the third and fourth quartile of plasma ferritin concentration compared to participants in the lowest quartile. Despite this, mean Anti-S IgG concentration was higher from 6 weeks to 3 months and remained high at 6 months, indicating a robust immune response. Seropositivity and neutralizing capacity at 6 months were generally consistent across quartiles of iron status. In addition, differences in antibody concentrations due to iron status were minor compared with other well-known determinants of vaccination efficacy. Although the clinical implications of our findings appear to be limited, our results are consistent with the view that iron status is associated with a more marked immune response following SARS-CoV-2 vaccination. Further research, including prospective studies with relevant clinical endpoints and focusing on iron-deficient populations, is needed.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p></sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>All procedures were approved by the ethics committee of the Canton of Zurich (BASEC 2021-00273) and written informed consent was obtained from all participants. The study was prospectively registered at the ISRCTN registry (ISRCTN 15499304).</p></sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>GP: Formal analysis, Writing &#x2013; original draft, Project administration, Data curation, Methodology, Visualization, Investigation, Funding acquisition, Writing &#x2013; review &amp; editing, Conceptualization. DMe: Conceptualization, Writing &#x2013; review &amp; editing, Methodology, Funding acquisition, Data curation, Formal analysis, Visualization. CF: Formal Analysis, Writing &#x2013; review &amp; editing, Visualization. PS: Writing &#x2013; review &amp; editing, Investigation. JB: Writing &#x2013; review &amp; editing, Formal analysis. SH: Writing &#x2013; review &amp; editing, Formal analysis. TB: Writing &#x2013; review &amp; editing. CZ: Validation, Methodology, Writing &#x2013; review &amp; editing, Investigation. NS: Conceptualization, Writing &#x2013; review &amp; editing, Methodology. MZ: Writing &#x2013; review &amp; editing, Conceptualization, Methodology. MP: Writing &#x2013; review &amp; editing, Funding acquisition. AF: Writing &#x2013; review &amp; editing. DMo: Conceptualization, Funding acquisition, Writing &#x2013; review &amp; editing, Writing &#x2013; original draft, Project administration, Visualization, Methodology.</p></sec>
<ack>
<title>Acknowledgments</title>
<p>We would like to thank the study administration team and the team of the reference vaccination center of the Canton of Zurich in Switzerland (Corona Center of the University of Zurich) for conducting the study as well as the study participants for their contribution to this research project. We also thank Nikolin Hilaj and Seline Keller for their contribution to the preparation of the samples for laboratory analyses.</p>
</ack>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The author MP declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.</p></sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p></sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fimmu.2026.1764884/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fimmu.2026.1764884/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="DataSheet1.pdf" id="SM1" mimetype="application/pdf"/></sec>
<ref-list>
<title>References</title>
<ref id="B1">
<label>1</label>
<mixed-citation publication-type="web">
<person-group person-group-type="author"><collab>Worldometer</collab>
</person-group>. <source>COVID-19 Coronavirus pandemic</source>. Available online at: <uri xlink:href="https://www.worldometers.info/coronavirus/">https://www.worldometers.info/coronavirus/</uri> (Accessed <date-in-citation content-type="access-date">February 18, 2025</date-in-citation>).
</mixed-citation>
</ref>
<ref id="B2">
<label>2</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Camaschella</surname> <given-names>C</given-names></name>
</person-group>. 
<article-title>Iron deficiency</article-title>. <source>Blood</source>. (<year>2019</year>) <volume>133</volume>:<page-range>30&#x2013;9</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1182/blood-2018-05-815944</pub-id>, PMID: <pub-id pub-id-type="pmid">30401704</pub-id>
</mixed-citation>
</ref>
<ref id="B3">
<label>3</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Milman</surname> <given-names>N</given-names></name>
<name><surname>Taylor</surname> <given-names>CL</given-names></name>
<name><surname>Merkel</surname> <given-names>J</given-names></name>
<name><surname>Brannon</surname> <given-names>PM</given-names></name>
</person-group>. 
<article-title>Iron status in pregnant women and women of reproductive age in Europe</article-title>. <source>Am J Clin Nutr</source>. (<year>2017</year>) <volume>106</volume>:<page-range>1655S&#x2013;62S</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.3945/ajcn</pub-id>, PMID: <pub-id pub-id-type="pmid">40433851</pub-id>
</mixed-citation>
</ref>
<ref id="B4">
<label>4</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Pasricha</surname> <given-names>SR</given-names></name>
<name><surname>Tye-Din</surname> <given-names>J</given-names></name>
<name><surname>Muckenthaler</surname> <given-names>MU</given-names></name>
<name><surname>Swinkels</surname> <given-names>DW</given-names></name>
</person-group>. 
<article-title>Iron deficiency</article-title>. <source>Lancet</source>. (<year>2021</year>) <volume>397</volume>:<page-range>233&#x2013;48</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/S0140-6736(20)32594-0</pub-id>, PMID: <pub-id pub-id-type="pmid">33285139</pub-id>
</mixed-citation>
</ref>
<ref id="B5">
<label>5</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Ahluwalia</surname> <given-names>N</given-names></name>
<name><surname>Sun</surname> <given-names>J</given-names></name>
<name><surname>Krause</surname> <given-names>D</given-names></name>
<name><surname>Mastro</surname> <given-names>A</given-names></name>
<name><surname>Handte</surname> <given-names>G</given-names></name>
</person-group>. 
<article-title>Immune function is impaired in iron-deficient, homebound, older women</article-title>. <source>Am J Clin Nutr</source>. (<year>2004</year>) <volume>79</volume>:<page-range>516&#x2013;21</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1093/ajcn/79.3.516</pub-id>, PMID: <pub-id pub-id-type="pmid">14985230</pub-id>
</mixed-citation>
</ref>
<ref id="B6">
<label>6</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Thibault</surname> <given-names>H</given-names></name>
<name><surname>Galan</surname> <given-names>P</given-names></name>
<name><surname>Selz</surname> <given-names>F</given-names></name>
<name><surname>Preziosi</surname> <given-names>P</given-names></name>
<name><surname>Olivier</surname> <given-names>C</given-names></name>
<name><surname>Badoual</surname> <given-names>J</given-names></name>
<etal/>
</person-group>. 
<article-title>The immune response in iron-deficient young children: effect of iron supplementation on cell-mediated immunity</article-title>. <source>Eur J Pediatr</source>. (<year>1993</year>) <volume>152</volume>:<page-range>120&#x2013;4</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1007/BF02072487</pub-id>, PMID: <pub-id pub-id-type="pmid">8444218</pub-id>
</mixed-citation>
</ref>
<ref id="B7">
<label>7</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Berger</surname> <given-names>J</given-names></name>
<name><surname>Dyck</surname> <given-names>JL</given-names></name>
<name><surname>Galan</surname> <given-names>P</given-names></name>
<name><surname>Aplogan</surname> <given-names>A</given-names></name>
<name><surname>Schneider</surname> <given-names>D</given-names></name>
<name><surname>Traissac</surname> <given-names>P</given-names></name>
<etal/>
</person-group>. 
<article-title>Effect of daily iron supplementation on iron status, cell-mediated immunity, and incidence of infections in 6&#x2013;36 month old Togolese children</article-title>. <source>Eur J Clin Nutr</source>. (<year>2000</year>) <volume>54</volume>:<fpage>29</fpage>&#x2013;<lpage>35</lpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/sj.ejcn.1600888</pub-id>, PMID: <pub-id pub-id-type="pmid">10694769</pub-id>
</mixed-citation>
</ref>
<ref id="B8">
<label>8</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Jabara</surname> <given-names>HH</given-names></name>
<name><surname>Boyden</surname> <given-names>SE</given-names></name>
<name><surname>Chou</surname> <given-names>J</given-names></name>
<name><surname>Ramesh</surname> <given-names>N</given-names></name>
<name><surname>Massaad</surname> <given-names>MJ</given-names></name>
<name><surname>Benson</surname> <given-names>H</given-names></name>
<etal/>
</person-group>. 
<article-title>A missense mutation in TFRC, encoding transferrin receptor 1, causes combined immunodeficiency</article-title>. <source>Nat Genet</source>. (<year>2015</year>) <volume>48</volume>:<page-range>74&#x2013;8</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/ng.3465</pub-id>, PMID: <pub-id pub-id-type="pmid">26642240</pub-id>
</mixed-citation>
</ref>
<ref id="B9">
<label>9</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Stoffel</surname> <given-names>NU</given-names></name>
<name><surname>Uyoga</surname> <given-names>MA</given-names></name>
<name><surname>Mutuku</surname> <given-names>FM</given-names></name>
<name><surname>Frost</surname> <given-names>JN</given-names></name>
<name><surname>Mwasi</surname> <given-names>E</given-names></name>
<name><surname>Paganini</surname> <given-names>D</given-names></name>
<etal/>
</person-group>. 
<article-title>Iron Deficiency Anemia at Time of Vaccination Predicts Decreased Vaccine Response and Iron Supplementation at Time of Vaccination Increases Humoral Vaccine Response: A Birth Cohort Study and a Randomized Trial Follow-Up Study in Kenyan Infants</article-title>. <source>Front Immunol</source>. (<year>2020</year>) <volume>11</volume>:<elocation-id>1313</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fimmu.2020.01313</pub-id>, PMID: <pub-id pub-id-type="pmid">32754150</pub-id>
</mixed-citation>
</ref>
<ref id="B10">
<label>10</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Frost</surname> <given-names>JN</given-names></name>
<name><surname>Tan</surname> <given-names>TK</given-names></name>
<name><surname>Abbas</surname> <given-names>M</given-names></name>
<name><surname>Wideman</surname> <given-names>SK</given-names></name>
<name><surname>Bonadonna</surname> <given-names>M</given-names></name>
<name><surname>Stoffel</surname> <given-names>NU</given-names></name>
<etal/>
</person-group>. 
<article-title>Hepcidin-mediated hypoferremia disrupts immune responses to vaccination and infection</article-title>. <source>Med</source>. (<year>2021</year>) <volume>2</volume>:<page-range>164&#x2013;79</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.medj.2020.10.004</pub-id>, PMID: <pub-id pub-id-type="pmid">33665641</pub-id>
</mixed-citation>
</ref>
<ref id="B11">
<label>11</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Jiang</surname> <given-names>Y</given-names></name>
<name><surname>Li</surname> <given-names>C</given-names></name>
<name><surname>Wu</surname> <given-names>Q</given-names></name>
<name><surname>An</surname> <given-names>P</given-names></name>
<name><surname>Huang</surname> <given-names>L</given-names></name>
<name><surname>Wang</surname> <given-names>J</given-names></name>
<etal/>
</person-group>. 
<article-title>Iron-dependent histone 3 lysine 9 demethylation controls B cell proliferation and humoral immune responses</article-title>. <source>Nat Commun</source>. (<year>2019</year>) <volume>10</volume>:<fpage>2935</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41467-019-11002-5</pub-id>, PMID: <pub-id pub-id-type="pmid">31270335</pub-id>
</mixed-citation>
</ref>
<ref id="B12">
<label>12</label>
<mixed-citation publication-type="web">
<person-group person-group-type="author">
<name><surname>Dufour</surname> <given-names>C</given-names></name>
<name><surname>Papadaki</surname> <given-names>H</given-names></name>
<name><surname>Warren</surname> <given-names>A</given-names></name>
<name><surname>Bradley</surname> <given-names>C</given-names></name>
<name><surname>Mecucci</surname> <given-names>C</given-names></name>
<name><surname>Palmblad</surname> <given-names>J</given-names></name>
<etal/>
</person-group>. <source>Expert opinions for COVID-19 vaccination in patients with non-malignant hematologic diseases</source>. Available online at: <uri xlink:href="https://ehaweb.org/covid-19/eha-statement-on-covid-19-vaccines/recommendations-for-covid-19-vaccination-in-patients-with-non-malignant-hematologic-diseases/">https://ehaweb.org/covid-19/eha-statement-on-covid-19-vaccines/recommendations-for-covid-19-vaccination-in-patients-with-non-malignant-hematologic-diseases/</uri> (Accessed <date-in-citation content-type="access-date">January 19, 2024</date-in-citation>).
</mixed-citation>
</ref>
<ref id="B13">
<label>13</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Drakesmith</surname> <given-names>H</given-names></name>
<name><surname>Pasricha</surname> <given-names>S-R</given-names></name>
<name><surname>Cabantchik</surname> <given-names>I</given-names></name>
<name><surname>Hershko</surname> <given-names>C</given-names></name>
<name><surname>Weiss</surname> <given-names>G</given-names></name>
<name><surname>Girelli</surname> <given-names>D</given-names></name>
<etal/>
</person-group>. 
<article-title>Vaccine efficacy and iron deficiency: an intertwined pair</article-title>? <source>Lancet Haematol</source>. (<year>2021</year>) <volume>8</volume>:<page-range>e666&#x2013;69</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/S2352-3026(21)00201-5</pub-id>, PMID: <pub-id pub-id-type="pmid">34450104</pub-id>
</mixed-citation>
</ref>
<ref id="B14">
<label>14</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Faizo</surname> <given-names>AA</given-names></name>
<name><surname>Bawazir</surname> <given-names>AA</given-names></name>
<name><surname>Almashjary</surname> <given-names>MN</given-names></name>
<name><surname>Hassan</surname> <given-names>AM</given-names></name>
<name><surname>Qashqari</surname> <given-names>FS</given-names></name>
<name><surname>Barefah</surname> <given-names>AS</given-names></name>
<etal/>
</person-group>. 
<article-title>Lack of evidence on association between iron deficiency and COVID-19 vaccine-induced neutralizing humoral immunity</article-title>. <source>Vaccines (Basel)</source>. (<year>2023</year>) <volume>11</volume>:<elocation-id>327</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3390/vaccines11020327</pub-id>, PMID: <pub-id pub-id-type="pmid">36851205</pub-id>
</mixed-citation>
</ref>
<ref id="B15">
<label>15</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>B&#xfc;rzle</surname> <given-names>O</given-names></name>
<name><surname>Menges</surname> <given-names>D</given-names></name>
<name><surname>Maier</surname> <given-names>JD</given-names></name>
<name><surname>Schams</surname> <given-names>D</given-names></name>
<name><surname>Puhan</surname> <given-names>MA</given-names></name>
<name><surname>Fehr</surname> <given-names>J</given-names></name>
<etal/>
</person-group>. 
<article-title>Adverse effects, perceptions and attitudes related to BNT162b2, mRNA-1273 or JNJ-78436735 SARS-CoV-2 vaccines: Population-based cohort</article-title>. <source>NPJ Vaccines</source>. (<year>2023</year>) <volume>8</volume>:<fpage>61</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41541-023-00657-3</pub-id>, PMID: <pub-id pub-id-type="pmid">37095137</pub-id>
</mixed-citation>
</ref>
<ref id="B16">
<label>16</label>
<mixed-citation publication-type="web">
<person-group person-group-type="author"><collab>Swiss Agency for Therapeutic Products Swissmedic</collab>
</person-group>. <source>Current status of authorisations for combating COVID-19</source>. Available online at: <uri xlink:href="https://www.swissmedic.ch/swissmedic/en/home/news/coronavirus-covid-19/stand-zl-bekaempfung-covid-19.html">https://www.swissmedic.ch/swissmedic/en/home/news/coronavirus-covid-19/stand-zl-bekaempfung-covid-19.html</uri> (Accessed <date-in-citation content-type="access-date">January 5, 2025</date-in-citation>).
</mixed-citation>
</ref>
<ref id="B17">
<label>17</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Erhardt</surname> <given-names>JG</given-names></name>
<name><surname>Estes</surname> <given-names>JE</given-names></name>
<name><surname>Pfeiffer</surname> <given-names>CM</given-names></name>
<name><surname>Biesalski</surname> <given-names>HK</given-names></name>
<name><surname>Craft</surname> <given-names>NE</given-names></name>
</person-group>. 
<article-title>Combined measurement of ferritin, soluble transferrin receptor, retinol binding protein, and C-reactive protein by an inexpensive, sensitive, and simple sandwich enzyme-linked immunosorbent assay technique</article-title>. <source>Nutr Method</source>. (<year>2004</year>) <volume>134</volume>:<page-range>3127&#x2013;32</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1093/jn/134.11.3127</pub-id>, PMID: <pub-id pub-id-type="pmid">15514286</pub-id>
</mixed-citation>
</ref>
<ref id="B18">
<label>18</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Mei</surname> <given-names>Z</given-names></name>
<name><surname>Addo</surname> <given-names>OY</given-names></name>
<name><surname>Jefferds</surname> <given-names>ME</given-names></name>
<name><surname>Sharma</surname> <given-names>AJ</given-names></name>
<name><surname>Flores-Ayala</surname> <given-names>RC</given-names></name>
<name><surname>Brittenham</surname> <given-names>GM</given-names></name>
</person-group>. 
<article-title>Physiologically based serum ferritin thresholds for iron deficiency in children and non-pregnant women: a US National Health and Nutrition Examination Surveys (NHANES) serial cross-sectional study</article-title>. <source>Lancet Haematol</source>. (<year>2021</year>) <volume>8</volume>:<page-range>e572&#x2013;82</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/S2352-3026(21)00168-X</pub-id>, PMID: <pub-id pub-id-type="pmid">34329578</pub-id>
</mixed-citation>
</ref>
<ref id="B19">
<label>19</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Yaw Addo</surname> <given-names>O</given-names></name>
<name><surname>Mei</surname> <given-names>Z</given-names></name>
<name><surname>Hod</surname> <given-names>EA</given-names></name>
<name><surname>Jefferds</surname> <given-names>ME</given-names></name>
<name><surname>Sharma</surname> <given-names>AJ</given-names></name>
<name><surname>Flores-Ayala</surname> <given-names>RC</given-names></name>
<etal/>
</person-group>. 
<article-title>Physiologically based serum ferritin thresholds for iron deficiency in women of reproductive age who are blood donors</article-title>. <source>Blood Adv</source>. (<year>2022</year>) <volume>6</volume>:<page-range>3661&#x2013;5</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1182/bloodadvances.2022007066</pub-id>, PMID: <pub-id pub-id-type="pmid">35404995</pub-id>
</mixed-citation>
</ref>
<ref id="B20">
<label>20</label>
<mixed-citation publication-type="book">
<person-group person-group-type="author"><collab>World Health Organization (WHO)</collab>
</person-group>. <source>WHO guideline on use of ferritin concentrations to assess iron status in individuals and populations</source>. <publisher-loc>Geneva</publisher-loc>: 
<publisher-name>World Health Organization</publisher-name> (<year>2020</year>).
</mixed-citation>
</ref>
<ref id="B21">
<label>21</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Cook</surname> <given-names>JD</given-names></name>
<name><surname>Flowers</surname> <given-names>CH</given-names></name>
<name><surname>Skikne</surname> <given-names>BS</given-names></name>
</person-group>. 
<article-title>The quantitative assessment of body iron</article-title>. <source>Blood</source>. (<year>2003</year>) <volume>101</volume>:<page-range>3359&#x2013;64</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1182/blood</pub-id>
</mixed-citation>
</ref>
<ref id="B22">
<label>22</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Shah</surname> <given-names>JS</given-names></name>
<name><surname>Soon</surname> <given-names>PS</given-names></name>
<name><surname>Marsh</surname> <given-names>DJ</given-names></name>
</person-group>. 
<article-title>Comparison of methodologies to detect low levels of hemolysis in serum for accurate assessment of serum microRNAs</article-title>. <source>PloS One</source>. (<year>2016</year>) <volume>11</volume>:<fpage>e0153200</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1371/journal.pone.0153200</pub-id>, PMID: <pub-id pub-id-type="pmid">27054342</pub-id>
</mixed-citation>
</ref>
<ref id="B23">
<label>23</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Menges</surname> <given-names>D</given-names></name>
<name><surname>Zens</surname> <given-names>KD</given-names></name>
<name><surname>Ballouz</surname> <given-names>T</given-names></name>
<name><surname>Caduff</surname> <given-names>N</given-names></name>
<name><surname>Llanas-Cornejo</surname> <given-names>D</given-names></name>
<name><surname>Aschmann</surname> <given-names>HE</given-names></name>
<etal/>
</person-group>. 
<article-title>Heterogenous humoral and cellular immune responses with distinct trajectories post-SARS-CoV-2 infection in a population-based cohort</article-title>. <source>Nat Commun</source>. (<year>2022</year>) <volume>13</volume>:<fpage>4855</fpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41467-022-32573-w</pub-id>, PMID: <pub-id pub-id-type="pmid">35982045</pub-id>
</mixed-citation>
</ref>
<ref id="B24">
<label>24</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Fenwick</surname> <given-names>C</given-names></name>
<name><surname>Croxatto</surname> <given-names>A</given-names></name>
<name><surname>Coste</surname> <given-names>AT</given-names></name>
<name><surname>Pojer</surname> <given-names>F</given-names></name>
<name><surname>Andr&#xe9;</surname> <given-names>C</given-names></name>
<name><surname>Pellaton</surname> <given-names>C</given-names></name>
<etal/>
</person-group>. 
<article-title>Changes in SARS-coV-2 spike versus nucleoprotein antibody responses impact the estimates of infections in population-based seroprevalence studies</article-title>. <source>J Virol</source>. (<year>2021</year>) <volume>95</volume>:<elocation-id>e01828-20</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1128/jvi.01828-20</pub-id>, PMID: <pub-id pub-id-type="pmid">33144321</pub-id>
</mixed-citation>
</ref>
<ref id="B25">
<label>25</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Fenwick</surname> <given-names>C</given-names></name>
<name><surname>Turelli</surname> <given-names>P</given-names></name>
<name><surname>Pellaton</surname> <given-names>C</given-names></name>
<name><surname>Farina</surname> <given-names>A</given-names></name>
<name><surname>Campos</surname> <given-names>J</given-names></name>
<name><surname>Raclot</surname> <given-names>C</given-names></name>
<etal/>
</person-group>. 
<article-title>A high-throughput cell-and virus-free assay shows reduced neutralization of SARS-CoV-2 variants by COVID-19 convalescent plasma</article-title>. <source>Sci Transl Med</source>. (<year>2021</year>) <volume>13</volume>:<elocation-id>8452</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1126/scitranslmed.abi8452</pub-id>, PMID: <pub-id pub-id-type="pmid">34257144</pub-id>
</mixed-citation>
</ref>
<ref id="B26">
<label>26</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Uchida</surname> <given-names>T</given-names></name>
<name><surname>Akitsuki</surname> <given-names>T</given-names></name>
<name><surname>Kimura</surname> <given-names>H</given-names></name>
<name><surname>Tanaka</surname> <given-names>T</given-names></name>
<name><surname>Matsuda</surname> <given-names>S</given-names></name>
<name><surname>Kaniyone</surname> <given-names>S</given-names></name>
</person-group>. 
<article-title>Relationship among plasma iron, plasma iron turnover, and reticuloendothelial iron release</article-title>. <source>Blood</source>. (<year>1983</year>) <volume>61</volume>:<fpage>799</fpage>&#x2013;<lpage>802</lpage>. doi:&#xa0;<pub-id pub-id-type="doi">10.1182/blood.V61.4.799.799</pub-id>, PMID: <pub-id pub-id-type="pmid">41496790</pub-id>
</mixed-citation>
</ref>
<ref id="B27">
<label>27</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Olafsdottir</surname> <given-names>TA</given-names></name>
<name><surname>Alexandersson</surname> <given-names>KF</given-names></name>
<name><surname>Sveinbjornsson</surname> <given-names>G</given-names></name>
<name><surname>Lapini</surname> <given-names>G</given-names></name>
<name><surname>Palladino</surname> <given-names>L</given-names></name>
<name><surname>Montomoli</surname> <given-names>E</given-names></name>
<etal/>
</person-group>. 
<article-title>Age and influenza-specific pre-vaccination antibodies strongly affect influenza vaccine responses in the Icelandic population whereas disease and medication have small effects</article-title>. <source>Front Immunol</source>. (<year>2018</year>) <volume>8</volume>:<elocation-id>1872</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fimmu.2017.01872</pub-id>, PMID: <pub-id pub-id-type="pmid">29358933</pub-id>
</mixed-citation>
</ref>
<ref id="B28">
<label>28</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Hanson</surname> <given-names>AL</given-names></name>
<name><surname>Mul&#xe8;</surname> <given-names>MP</given-names></name>
<name><surname>Ruffieux</surname> <given-names>H</given-names></name>
<name><surname>Mescia</surname> <given-names>F</given-names></name>
<name><surname>Bergamaschi</surname> <given-names>L</given-names></name>
<name><surname>Pelly</surname> <given-names>VS</given-names></name>
<etal/>
</person-group>. 
<article-title>Iron dysregulation and inflammatory stress erythropoiesis associates with long-term outcome of COVID-19</article-title>. <source>Nat Immunol</source>. (<year>2024</year>) <volume>25</volume>:<page-range>471&#x2013;82</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1038/s41590-024-01754-8</pub-id>, PMID: <pub-id pub-id-type="pmid">38429458</pub-id>
</mixed-citation>
</ref>
<ref id="B29">
<label>29</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Foley</surname> <given-names>PW</given-names></name>
<name><surname>Kalra</surname> <given-names>PR</given-names></name>
<name><surname>Cleland</surname> <given-names>JGF</given-names></name>
<name><surname>Petrie</surname> <given-names>MC</given-names></name>
<name><surname>Kalra</surname> <given-names>PA</given-names></name>
<name><surname>Squire</surname> <given-names>I</given-names></name>
<etal/>
</person-group>. 
<article-title>Effect of correcting iron deficiency on the risk of serious infection in heart failure: Insights from the IRONMAN trial</article-title>. <source>Eur J Heart Fail</source>. (<year>2024</year>) <volume>27</volume>:<page-range>166&#x2013;73</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1002/ejhf.3504</pub-id>, PMID: <pub-id pub-id-type="pmid">39453738</pub-id>
</mixed-citation>
</ref>
<ref id="B30">
<label>30</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>El-Battrawy</surname> <given-names>I</given-names></name>
<name><surname>Longo</surname> <given-names>F</given-names></name>
<name><surname>N&#xfa;&#xf1;ez Gil</surname> <given-names>IJ</given-names></name>
<name><surname>Abumayyaleh</surname> <given-names>M</given-names></name>
<name><surname>Gianesin</surname> <given-names>B</given-names></name>
<name><surname>Estrada</surname> <given-names>V</given-names></name>
<etal/>
</person-group>. 
<article-title>Thalassaemia is paradoxically associated with a reduced risk of in-hospital complications and mortality in COVID-19: Data from an international registry</article-title>. <source>J Cell Mol Med</source>. (<year>2022</year>) <volume>26</volume>:<page-range>2520&#x2013;8</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1111/jcmm.17026</pub-id>, PMID: <pub-id pub-id-type="pmid">35355397</pub-id>
</mixed-citation>
</ref>
<ref id="B31">
<label>31</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Santos-Ara&#xfa;jo</surname> <given-names>C</given-names></name>
<name><surname>Mota Veiga</surname> <given-names>P</given-names></name>
<name><surname>Santos</surname> <given-names>MJ</given-names></name>
<name><surname>Santos</surname> <given-names>L</given-names></name>
<name><surname>Rom&#xe3;ozinho</surname> <given-names>C</given-names></name>
<name><surname>Silva</surname> <given-names>M</given-names></name>
<etal/>
</person-group>. 
<article-title>Time-dependent evolution of IgG antibody levels after first and second dose of mRNA-based SARS-CoV-2 vaccination in haemodialysis patients: A multicentre study</article-title>. <source>Nephrol Dialysis Transplant</source>. (<year>2022</year>) <volume>37</volume>:<page-range>375&#x2013;81</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1093/ndt/gfab293</pub-id>, PMID: <pub-id pub-id-type="pmid">34634116</pub-id>
</mixed-citation>
</ref>
<ref id="B32">
<label>32</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Drakesmith</surname> <given-names>H</given-names></name>
<name><surname>Prentice</surname> <given-names>AM</given-names></name>
</person-group>. 
<article-title>Hepcidin and the iron-infection axis</article-title>. <source>Sci (1979)</source>. (<year>2012</year>) <volume>338</volume>:<page-range>768&#x2013;72</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1126/science.1224577</pub-id>, PMID: <pub-id pub-id-type="pmid">23139325</pub-id>
</mixed-citation>
</ref>
<ref id="B33">
<label>33</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Stoffel</surname> <given-names>NU</given-names></name>
<name><surname>Drakesmith</surname> <given-names>H</given-names></name>
</person-group>. 
<article-title>Effects of iron status on adaptive immunity and vaccine efficacy: A review</article-title>. <source>Adv Nutr</source>. (<year>2024</year>) <volume>15</volume>:<elocation-id>100238</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.advnut.2024.100238</pub-id>, PMID: <pub-id pub-id-type="pmid">38729263</pub-id>
</mixed-citation>
</ref>
<ref id="B34">
<label>34</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Vinke</surname> <given-names>JSJ</given-names></name>
<name><surname>Altulea</surname> <given-names>DHA</given-names></name>
<name><surname>Eisenga</surname> <given-names>MF</given-names></name>
<name><surname>Jagersma</surname> <given-names>RL</given-names></name>
<name><surname>Niekolaas</surname> <given-names>TM</given-names></name>
<name><surname>van Baarle</surname> <given-names>D</given-names></name>
<etal/>
</person-group>. 
<article-title>Ferric carboxymaltose and SARS-CoV-2 vaccination-induced immunogenicity in kidney transplant recipients with iron deficiency: the COVAC-EFFECT randomized controlled trial</article-title>. <source>Front Immunol</source>. (<year>2023</year>) <volume>13</volume>:<elocation-id>1017178</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.3389/fimmu.2022.1017178</pub-id>, PMID: <pub-id pub-id-type="pmid">36618359</pub-id>
</mixed-citation>
</ref>
<ref id="B35">
<label>35</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Tene</surname> <given-names>L</given-names></name>
<name><surname>Karasik</surname> <given-names>A</given-names></name>
<name><surname>Chodick</surname> <given-names>G</given-names></name>
<name><surname>Pereira</surname> <given-names>DIA</given-names></name>
<name><surname>Schou</surname> <given-names>H</given-names></name>
<name><surname>Waechter</surname> <given-names>S</given-names></name>
<etal/>
</person-group>. 
<article-title>Iron deficiency and the effectiveness of the BNT162b2 vaccine for SARS-CoV-2 infection: A retrospective, longitudinal analysis of real-world data</article-title>. <source>PloS One</source>. (<year>2023</year>) <volume>18</volume>:<elocation-id>e0285606</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1371/journal.pone.0285606</pub-id>, PMID: <pub-id pub-id-type="pmid">37216375</pub-id>
</mixed-citation>
</ref>
<ref id="B36">
<label>36</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Polack</surname> <given-names>FP</given-names></name>
<name><surname>Thomas</surname> <given-names>SJ</given-names></name>
<name><surname>Kitchin</surname> <given-names>N</given-names></name>
<name><surname>Absalon</surname> <given-names>J</given-names></name>
<name><surname>Gurtman</surname> <given-names>A</given-names></name>
<name><surname>Lockhart</surname> <given-names>S</given-names></name>
<etal/>
</person-group>. 
<article-title>Safety and efficacy of the BNT162b2 mRNA covid-19 vaccine</article-title>. <source>New Engl J Med</source>. (<year>2020</year>) <volume>383</volume>:<page-range>2603&#x2013;15</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1056/nejmoa2034577</pub-id>, PMID: <pub-id pub-id-type="pmid">33301246</pub-id>
</mixed-citation>
</ref>
<ref id="B37">
<label>37</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Baden</surname> <given-names>LR</given-names></name>
<name><surname>El Sahly</surname> <given-names>HM</given-names></name>
<name><surname>Essink</surname> <given-names>B</given-names></name>
<name><surname>Kotloff</surname> <given-names>K</given-names></name>
<name><surname>Frey</surname> <given-names>S</given-names></name>
<name><surname>Novak</surname> <given-names>R</given-names></name>
<etal/>
</person-group>. 
<article-title>Efficacy and safety of the mRNA-1273 SARS-coV-2 vaccine</article-title>. <source>New Engl J Med</source>. (<year>2021</year>) <volume>384</volume>:<page-range>403&#x2013;16</page-range>. doi:&#xa0;<pub-id pub-id-type="doi">10.1056/nejmoa2035389</pub-id>, PMID: <pub-id pub-id-type="pmid">33378609</pub-id>
</mixed-citation>
</ref>
<ref id="B38">
<label>38</label>
<mixed-citation publication-type="journal">
<person-group person-group-type="author">
<name><surname>Mahroum</surname> <given-names>N</given-names></name>
<name><surname>Alghory</surname> <given-names>A</given-names></name>
<name><surname>Kiyak</surname> <given-names>Z</given-names></name>
<name><surname>Alwani</surname> <given-names>A</given-names></name>
<name><surname>Seida</surname> <given-names>R</given-names></name>
<name><surname>Alrais</surname> <given-names>M</given-names></name>
<etal/>
</person-group>. 
<article-title>Ferritin &#x2013; from iron, through inflammation and autoimmunity, to COVID-19</article-title>. <source>J Autoimmun</source>. (<year>2022</year>) <volume>126</volume>:<elocation-id>102778</elocation-id>. doi:&#xa0;<pub-id pub-id-type="doi">10.1016/j.jaut.2021.102778</pub-id>, PMID: <pub-id pub-id-type="pmid">34883281</pub-id>
</mixed-citation>
</ref>
</ref-list>
<fn-group>
<fn id="n1" fn-type="custom" custom-type="edited-by">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/109169">Rehan Khan</ext-link>, Rutgers University, United States</p></fn>
<fn id="n2" fn-type="custom" custom-type="reviewed-by">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2737424">Suzan Farhang-Sardroodi</ext-link>, The University of Toronto, Canada</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3276047">Hatice Nur Halip&#xe7;i Topsakal</ext-link>, Bezmialem Vak&#x131;f University, T&#xfc;rkiye</p></fn>
</fn-group>
<fn-group>
<fn fn-type="abbr" id="abbrev1">
<label>Abbreviations:</label>
<p>AGP, alpha(1)-acid glycoprotein; BL, baseline; BMI, body mass index; CI, confidence interval; CRP, c-reactive protein; IC, inhibitory concentration; ICP-MS, inductively coupled plasma-mass spectrometry; MFI, mean fluorescence intensity; NAb, neutralizing antibodies; PBMCs, peripheral blood mononuclear cells; Q, quartile; RBP, retinol binding protein; REDCap, Research Electronic Data Capture platform; S, spike; SARS-CoV-2, Severe acute respiratory syndrome coronavirus 2; SD, standard deviation; sTfR, soluble transferrin receptor; TfR1, transferrin receptor 1.</p>
</fn>
</fn-group>
</back>
</article>