Preparing for Life: Plasma Proteome Changes and Immune System Development During the First Week of Human Life

Tue Bjerg Bennike, Benoit Fatou, Asimenia Angelidou, Joann Diray-Arce, Reza Falsafi, Rebecca Ford, Erin E Gill, Simon D van Haren, Olubukola T Idoko, Amy H Lee, Rym Ben-Othman, William S Pomat, Casey P Shannon, Kinga K Smolen, Scott J Tebbutt, Al Ozonoff, Peter C Richmond, Anita H J van den Biggelaar, Robert E W Hancock, Beate Kampmann, Tobias R Kollmann, Ofer Levy, Hanno Steen, Tue Bjerg Bennike, Benoit Fatou, Asimenia Angelidou, Joann Diray-Arce, Reza Falsafi, Rebecca Ford, Erin E Gill, Simon D van Haren, Olubukola T Idoko, Amy H Lee, Rym Ben-Othman, William S Pomat, Casey P Shannon, Kinga K Smolen, Scott J Tebbutt, Al Ozonoff, Peter C Richmond, Anita H J van den Biggelaar, Robert E W Hancock, Beate Kampmann, Tobias R Kollmann, Ofer Levy, Hanno Steen

Abstract

Neonates have heightened susceptibility to infections. The biological mechanisms are incompletely understood but thought to be related to age-specific adaptations in immunity due to resource constraints during immune system development and growth. We present here an extended analysis of our proteomics study of peripheral blood-plasma from a study of healthy full-term newborns delivered vaginally, collected at the day of birth and on day of life (DOL) 1, 3, or 7, to cover the first week of life. The plasma proteome was characterized by LC-MS using our established 96-well plate format plasma proteomics platform. We found increasing acute phase proteins and a reduction of respective inhibitors on DOL1. Focusing on the complement system, we found increased plasma concentrations of all major components of the classical complement pathway and the membrane attack complex (MAC) from birth onward, except C7 which seems to have near adult levels at birth. In contrast, components of the lectin and alternative complement pathways mainly decreased. A comparison to whole blood messenger RNA (mRNA) levels enabled characterization of mRNA and protein levels in parallel, and for 23 of the 30 monitored complement proteins, the whole blood transcript information by itself was not reflective of the plasma protein levels or dynamics during the first week of life. Analysis of immunoglobulin (Ig) mRNA and protein levels revealed that IgM levels and synthesis increased, while the plasma concentrations of maternally transferred IgG1-4 decreased in accordance with their in vivo half-lives. The neonatal plasma ratio of IgG1 to IgG2-4 was increased compared to adult values, demonstrating a highly efficient IgG1 transplacental transfer process. Partial compensation for maternal IgG degradation was achieved by endogenous synthesis of the IgG1 subtype which increased with DOL. The findings were validated in a geographically distinct cohort, demonstrating a consistent developmental trajectory of the newborn's immune system over the first week of human life across continents. Our findings indicate that the classical complement pathway is central for newborn immunity and our approach to characterize the plasma proteome in parallel with the transcriptome will provide crucial insight in immune ontogeny and inform new approaches to prevent and treat diseases.

Keywords: complement; immunoglobulin; inhibitors; innate immune system; membrane attack complex (MAC); ontogeny; proteomics; terminal complement complex (SC5b-9).

Copyright © 2020 Bennike, Fatou, Angelidou, Diray-Arce, Falsafi, Ford, Gill, van Haren, Idoko, Lee, Ben-Othman, Pomat, Shannon, Smolen, Tebbutt, Ozonoff, Richmond, Biggelaar, Hancock, Kampmann, Kollmann, Levy and Steen.

Figures

Figure 1
Figure 1
Study design and number of enrolled newborns in the main cohort enrolled in The Gambia.
Figure 2
Figure 2
Principal component analysis (PCA) plot of all quantifiable proteins separates samples by day of life (DOL). PC, principal component. Explained variance given in percentages.
Figure 3
Figure 3
Differentially abundant plasma proteins (q-value (A) We identified a robust trajectory of differentially expressed proteins over the first week of life. (B) Overlap of regulated proteins. Protein regulations of (C) Haptoglobin (HP). (D) Serum amyloid A1 (SAA1) normalized to DOL0, with mean abundance difference indicated by dots connected with a line. q-value * <0.05, **: <0.01, ***: <0.001.
Figure 4
Figure 4
Clustered Pearson’s protein-protein correlation matrix of protein changes during the first week of life, of all quantifiable proteins (on the x- and y-axis) which allows for identifying proteins with similar trajectories across all samples. Several clusters of correlating proteins were identified, including a cluster centered around hemoglobin and an acute phase response cluster including SAA1 and SAA2.
Figure 5
Figure 5
Analysis of protein-protein interactions of the differentiating proteins at (A) DOL1, (B) DOL3, and (C) DOL7 compared to DOL0 (at birth). SAA1 which was regulated at DOL1 only is indicated with an arrow, and lines indicate interacting proteins. Proteins tagged as complement system in Gene Ontology are indicated with black boxes without further curation.
Figure 6
Figure 6
Simplified scheme of the three activation- and terminal complement pathway. Inhibitors in blue italic.
Figure 7
Figure 7
Average change of complement proteins grouped by their function across the first week of life compared to DOL0. (A) classical pathway, (B) lectin pathway, and (C) alternative pathway. (D) Membrane attack complex (MAC) proteins, (E) complement inhibitors. Pathway activations from Gene Ontology without further curation.
Figure 8
Figure 8
Divergence of complement plasma protein and whole blood messenger RNA (mRNA) levels, as compared to DOL0, of the 11 complement proteins with detected whole blood mRNA.
Figure 9
Figure 9
Protein and messenger RNA (mRNA) levels (dotted line) of (A) IgM, (B) J chain, (C) IgG1 across the first week of life compared to DOL0, with mean abundance difference indicated by dots connected by lines. Protein to RNA correlation and p-value given. Statistics compared to DOL0: q-value protein (mRNA) <0.05: *(*), <0.01: **(**), <0.001: ***(***).
Figure 10
Figure 10
Protein levels of (A–D) IgG1-4 across the first week of life as compared to DOL0, with mean abundance difference indicated by dots connected by solid line. (E) Comparison of the ratios of IgG1-4 normalized to IgG2 between adult-levels (purple) and newborn-levels at DOL0 (gray), or (F) DOL7 (blue). Statistics A–D (E, F): q-value <0.05: *, <0.01: **, <0.001: ***.

References

    1. Zhang X, Zhivaki D, Lo-Man R. Unique aspects of the perinatal immune system. Nat Rev Immunol (2017) 17(8):495–507. 10.1038/nri.2017.54
    1. Kollmann TR, Kampmann B, Mazmanian SK, Marchant A, Levy O. Protecting the Newborn and Young Infant from Infectious Diseases: Lessons from Immune Ontogeny. Immunity (2017) 21 46(3):350–63. 10.1016/j.immuni.2017.03.009
    1. Balbus JM, Barouki R, Birnbaum LS, Etzel RA, Gluckman SPD, Grandjean P, et al. Early-life prevention of non-communicable diseases. Lancet (2013) 381:3–4. 10.1016/S0140-6736(12)61609-2
    1. Zinkernagel RM. Maternal antibodies, childhood infections, and autoimmune diseases. N Engl J Med (2001) 345(18):1331–5. 10.1056/NEJMra012493
    1. McGreal EP, Hearne K, Spiller OB. Off to a slow start: Under-development of the complement system in term newborns is more substantial following premature birth. Immunobiology (2012) 217(2):176–86. 10.1016/j.imbio.2011.07.027
    1. Maródi L. Neonatal Innate Immunity to Infectious Agents. Infect Immun (2006) 74(4):1999–2006. 10.1128/IAI.74.4.1999-2006.2006
    1. Lee AH, Shannon CP, Amenyogbe N, Bennike TB, Diray-Arce J, Idoko OT, et al. Dynamic molecular changes during the first week of human life follow a robust developmental trajectory. Nat Commun (2019) 10(1):1092. 10.1038/s41467-019-08794-x
    1. Carr EJ, Dooley J, Garcia-Perez JE, Lagou V, Lee JC, Wouters C, et al. The cellular composition of the human immune system is shaped by age and cohabitation. Nat Immunol (2016) 17(4):461–8. 10.1038/ni.3371
    1. Idoko OT, Smolen KK, Wariri O, Imam A, Shannon CP, Dibassey T, et al. Clinical Protocol for a Longitudinal Cohort Study Employing Systems Biology to Identify Markers of Vaccine Immunogenicity in Newborn Infants in The Gambia and Papua New Guinea. Front Pediatr (2020) 8:197. 10.3389/fped.2020.00197
    1. Bennike TB, Bellin MD, Xuan Y, Stensballe A, Møller FT, Beilman GJ, et al. A Cost-Effective High-Throughput Plasma and Serum Proteomics Workflow Enables Mapping of the Molecular Impact of Total Pancreatectomy with Islet Autotransplantation. J Proteome Res (2018) 04 17(5):1983–92. 10.1021/acs.jproteome.8b00111
    1. Bennike TB, Steen H. High-Throughput Parallel Proteomic Sample Preparation Using 96-Well Polyvinylidene Fluoride (PVDF) Membranes and C18 Purification Plates. In: Greening DW, Simpson RJ, editors. Serum/Plasma Proteomics. New York, NY: Springer New York; (2017). p. 395–402. 10.1074/mcp.O115.049650
    1. Cox J, Hein MY, Luber CA, Paron I, Nagaraj N, Mann M. Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ. Mol Cell Proteomics MCP (2014) 13(9):2513–26. 10.1074/mcp.M113.031591
    1. Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M. Andromeda: A Peptide Search Engine Integrated into the MaxQuant Environment. J Proteome Res (2011) 10(4):1794–805. 10.1021/pr101065j
    1. Gupta N, Pevzner PA. False Discovery Rates of Protein Identifications: A Strike against the Two-Peptide Rule. J Proteome Res (2009) 8(9):4173–81. 10.1021/pr9004794
    1. RStudio Team RStudio: Integrated Development Environment for R. Boston, MA: RStudio, Inc; (2015). Available at: .
    1. R Core Team R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; (2015). Available at: .
    1. Lazar C, Gatto L, Ferro M, Bruley C, Burger T. Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies. J Proteome Res (2016) 15(4):1116–25. 10.1021/acs.jproteome.5b00981
    1. Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics (2007) 8(1):118–27. 10.1093/biostatistics/kxj037
    1. Hicks SC, Irizarry RA. quantro: a data-driven approach to guide the choice of an appropriate normalization method. Genome Biol (2015) 16:117. 10.1186/s13059-015-0679-0
    1. Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag; (2009). 266 p. 10.1007/978-0-387-98141-3
    1. Wickham H, François R, Henry L, Müller K. dplyr: A Grammar of Data Manipulation. R package version 0.7.6. Boston, MA: (2018). Available at: .
    1. Rohart F, Gautier B, Singh A, Lê Cao K-A. mixOmics: An R package for ‘omics feature selection and multiple data integration. PloS Comput Biol (2017) 13(11):e1005752. 10.1371/journal.pcbi.1005752
    1. Vizcaíno JA, Deutsch EW, Wang R, Csordas A, Reisinger F, Ríos D, et al. ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat Biotechnol (2014) 32:223–6. 10.1038/nbt.2839
    1. Vizcaíno JA, Csordas A, del-Toro N, Dianes JA, Griss J, Lavidas I, et al. update of the PRIDE database and its related tools. Nucleic Acids Res (2016) 44:D447–56. 10.1093/nar/gkv1145
    1. Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. J Stat Software (2015) 67(1):1–48. 10.18637/jss.v067.i01
    1. Benjamini Y, Krieger AM, Yekutieli D. Adaptive linear step-up procedures that control the false discovery rate. Biometrika (2006) 93(3):491–507. 10.1093/biomet/93.3.491
    1. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res (2003) 13(11):2498–504. 10.1101/gr.1239303
    1. Liao Y, Wang J, Jaehnig EJ, Shi Z, Zhang B. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. Nucleic Acids Res (2019) 47(W1):W199–205. 10.1093/nar/gkz401
    1. Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res (2015) 43(D1):D447–52. 10.1093/nar/gku1003
    1. Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics (2016) 32(19):3047–8. 10.1093/bioinformatics/btw354
    1. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics (2013) 29(1):15–21. 10.1093/bioinformatics/bts635
    1. Anders S, Pyl PT, Huber W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics (2015) 31(2):166–9. 10.1093/bioinformatics/btu638
    1. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol (2014) 15(12):550. 10.1186/s13059-014-0550-8
    1. Yasui K, Matsumoto K, Hirayama F, Tani Y, Nakano T. Differences Between Peripheral Blood and Cord Blood in the Kinetics of Lineage-Restricted Hematopoietic Cells: Implications for Delayed Platelet Recovery Following Cord Blood Transplantation. Stem Cells (2003) 21(2):143–51. 10.1634/stemcells.21-2-143
    1. Bennike T, Ayturk U, Haslauer CM, Froehlich JW, Proffen BL, Barnaby O, et al. A normative study of the synovial fluid proteome from healthy porcine knee joints. J Proteome Res (2014) 13(10):4377–87. 10.1021/pr500587x
    1. Bennike TB, Barnaby O, Steen H, Stensballe A. Characterization of the porcine synovial fluid proteome and a comparison to the plasma proteome. Data Brief (2015) Dec 5:241–7. 10.1016/j.dib.2015.08.028
    1. Zhou M, Lucas DA, Chan KC, Issaq HJ, Petricoin EF, Liotta LA, et al. An investigation into the human serum “interactome.” ELECTROPHORESIS (2004) 25(9):1289–98. 10.1002/elps.200405866
    1. Kirov S, Sasson A, Zhang C, Chasalow S, Dongre A, Steen H, et al. Degradation of the extracellular matrix is part of the pathology of ulcerative colitis. Mol Omics (2019) 15(1):67–76. 10.1039/c8mo00239h
    1. Jeanmougin M, de Reynies A, Marisa L, Paccard C, Nuel G, Guedj M. Should We Abandon the t-Test in the Analysis of Gene Expression Microarray Data: A Comparison of Variance Modeling Strategies. PloS One (2010) 5(9):e12336. 10.1371/journal.pone.0012336
    1. Peri KG, Gagnon C, Bard H. Quantitative Correlation between Globin mRNAs and Synthesis of Fetal and Adult Hemoglobins during Hemoglobin Switchover in the Perinatal Period. Pediatr Res (1998) 43(4):504–8. 10.1203/00006450-199804000-00011
    1. Chavez-Bueno S, Beasley JA, Goldbeck JM, Bright BC, Morton DJ, Whitby PW, et al. Haptoglobin concentrations in preterm and term newborns. J Perinatol: Official Journal of the California Perinatal Association (2011) 31(7):500–3. 10.1038/jp.2010.197
    1. Ignjatovic V, Lai C, Summerhayes R, Mathesius U, Tawfilis S, Perugini MA, et al. Age-Related Differences in Plasma Proteins: How Plasma Proteins Change from Neonates to Adults. Uversky V, editor. PloS One (2011) 6(2):e17213. 10.1371/journal.pone.0017213
    1. Schaer DJ, Buehler PW, Alayash AI, Belcher JD, Vercellotti GM. Hemolysis and free hemoglobin revisited: exploring hemoglobin and hemin scavengers as a novel class of therapeutic proteins. Blood (2013) 121(8):1276–84. 10.1182/blood-2012-11-451229
    1. Kristiansen M, Graversen JH, Jacobsen C, Sonne O, Hoffman HJ, Law SK, et al. Identification of the haemoglobin scavenger receptor. Nature (2001) 409(6817):198–201. 10.1038/35051594
    1. Li W, Wang W, Zuo R, Liu C, Shu Q, Ying H, et al. Induction of pro-inflammatory genes by serum amyloid A1 in human amnion fibroblasts. Sci Rep (2017) 7:693. 10.1038/s41598-017-00782-9
    1. Sack GH. Serum amyloid A – a review. Mol Med (2018) 24:46. 10.1186/s10020-018-0047-0
    1. Jumeau C, Awad F, Assrawi E, Cobret L, Duquesnoy P, Giurgea I, et al. Expression of SAA1, SAA2 and SAA4 genes in human primary monocytes and monocyte-derived macrophages. PloS One (2019) 14:e0217005. 10.1371/journal.pone.0217005
    1. Marchini G, Berggren V, Djilali-Merzoug R, Hansson L-O. The birth process initiates an acute phase reaction in the fetus-newborn infant. Acta Paediatr (2000) 89(9):1082–6. 10.1111/j.1651-2227.2000.tb03355.x
    1. Pettengill MA, van Haren SD, Levy O. Soluble mediators regulating immunity in early life. Front Immunol (2014) 5:457. 10.3389/fimmu.2014.00457
    1. Levy O. Innate immunity of the newborn: basic mechanisms and clinical correlates. Nat Rev Immunol (2007) 7(5):379–90. 10.1038/nri2075
    1. Gorevic PD. Amyloid and inflammation. Proc Natl Acad Sci (2013) 110(41):16291–2. 10.1073/pnas.1315112110
    1. Tape C, Tan R, Neshejm M, Kisilevsky R. Direct Evidence for Circulating apoSAA as the Precursor of Tissue AA Amyloid Deposits. Scand J Immunol (1988) 28(3):317–24. 10.1111/j.1365-3083.1988.tb01455.x
    1. Castell JV, Gómez-Lechón MJ, David M, Andus T, Geiger T, Trullenque R, et al. Interleukin-6 is the major regulator of acute phase protein synthesis in adult human hepatocytes. FEBS Lett (1989) 242(2):237–9. 10.1016/0014-5793(89)80476-4
    1. Merle NS, Church SE, Fremeaux-Bacchi V, Roumenina LT. Complement System Part I – Molecular Mechanisms of Activation and Regulation. Front Immunol (2015) 6:262. 10.3389/fimmu.2015.00262
    1. Palmeira P, Quinello C, Silveira-Lessa AL, Zago CA, Carneiro-Sampaio M. IgG Placental Transfer in Healthy and Pathological Pregnancies. Clin Dev Immunol (2012) 2012:985646. 10.1155/2012/985646
    1. Pernemalm M, Sandberg A, Zhu Y, Boekel J, Tamburro D, Schwenk JM, et al. In-depth human plasma proteome analysis captures tissue proteins and transfer of protein variants across the placenta. eLife (2019) 8. 10.7554/eLife.41608
    1. Ferguson JS, Weis JJ, Martin JL, Schlesinger LS. Complement Protein C3 Binding to Mycobacterium tuberculosis Is Initiated by the Classical Pathway in Human Bronchoalveolar Lavage Fluid. Infect Immun (2004) 72(5):2564–73. 10.1128/IAI.72.5.2564-2573.2004
    1. Lubbers R, van Essen MF, van Kooten C, Trouw LA. Production of complement components by cells of the immune system. Clin Exp Immunol (2017) 188(2):183–94. 10.1111/cei.12952
    1. Roos MH, Mollenhauer E, Démant P, Rittner C. A molecular basis for the two locus model of human complement component C4. Nature (1982) 298(5877):854–6. 10.1038/298854a0
    1. Law SK, Dodds AW, Porter RR. A comparison of the properties of two classes, C4A and C4B, of the human complement component C4. EMBO J (1984) 3(8):1819–23. 10.1002/j.1460-2075.1984.tb02052.x
    1. Rupert KL, Moulds JM, Yang Y, Arnett FC, Warren RW, Reveille JD, et al. The Molecular Basis of Complete Complement C4A and C4B Deficiencies in a Systemic Lupus Erythematosus Patient with Homozygous C4A and C4B Mutant Genes. J Immunol (2002) 169(3):1570–8. 10.4049/jimmunol.169.3.1570
    1. Beltrame MH, Catarino SJ, Goeldner I, Boldt ABW, de Messias-Reason IJ. The Lectin Pathway of Complement and Rheumatic Heart Disease. Front Pediatr (2015) 2:148. 10.3389/fped.2014.00148
    1. Szala A, Sawicki S, Swierzko AST, Szemraj J, Sniadecki M, Michalski M, et al. Ficolin-2 and ficolin-3 in women with malignant and benign ovarian tumours. Cancer Immunol Immunother (2013) 62(8):1411–9. 10.1007/s00262-013-1445-3
    1. Sallenbach S, Thiel S, Aebi C, Otth M, Bigler S, Jensenius JC, et al. Serum concentrations of lectin-pathway components in healthy neonates, children and adults: mannan-binding lectin (MBL), M-, L-, and H-ficolin, and MBL-associated serine protease-2 (MASP-2). Pediatr Allergy Immunol (2011) 22(4):424–30. 10.1111/j.1399-3038.2010.01104.x
    1. Frakking FNJ, Brouwer N, Zweers D, Merkus MP, Kuijpers TW, Offringa M, et al. High prevalence of mannose-binding lectin (MBL) deficiency in premature neonates. Clin Exp Immunol (2006) 145(1):5–12. 10.1111/j.1365-2249.2006.03093.x
    1. Kilpatrick DC, Liston WA, Midgley PC. Mannan-binding protein in human umbilical cord blood. Nat Immun 1996 (1997) 15(5):234–40. 10.1111/j.1365-2249.2006.03093.x
    1. Michalski M, Szala A, St. Swierzko A, Lukasiewicz J, Maciejewska A, Kilpatrick DC, et al. H-ficolin (ficolin-3) concentrations and FCN3 gene polymorphism in neonates. Immunobiology (2012) 217(7):730–7. 10.1016/j.imbio.2011.12.004
    1. Cedzynski M, Swierzko AST, Kilpatrick DC. Factors of the Lectin Pathway of Complement Activation and Their Clinical Associations in Neonates. J BioMed Biotechnol (2012) 2012:363246. 10.1155/2012/363246
    1. Medicus RG, Götze O, Müller-Eberhard HJ. Alternative pathway of complement: recruitment of precursor properdin by the labile C3/C5 convertase and the potentiation of the pathway. J Exp Med (1976) 144(4):1076–93. 10.1084/jem.144.4.1076
    1. Camous L, Roumenina L, Bigot S, Brachemi S, Frémeaux-Bacchi V, Lesavre P, et al. Complement alternative pathway acts as a positive feedback amplification of neutrophil activation. Blood (2011) 117(4):1340–9. 10.1182/blood-2010-05-283564
    1. Wirthmueller U, Dewald B, Thelen M, Schäfer MK, Stover C, Whaley K, et al. Properdin, a positive regulator of complement activation, is released from secondary granules of stimulated peripheral blood neutrophils. J Immunol Baltim Md 1950 (1997) 158(9):4444–51.
    1. Lachmann PJ, Thompson RA. Reactive lysis: the complement-mediated lysis of unsensitized cells. II. The characterization of activated reactor as C56 and the participation of C8 and C9. J Exp Med (1970) 131(4):643–57. 10.1084/jem.131.4.643
    1. Terai I, Kobayashi K, Matsushita M, Fujita T, Matsuno K. alpha 2-Macroglobulin binds to and inhibits mannose-binding protein-associated serine protease. Int Immunol (1995) 7(10):1579–84. 10.1093/intimm/7.10.1579
    1. Paréj K, Dobó J, Závodszky P, Gál P. The control of the complement lectin pathway activation revisited: both C1-inhibitor and antithrombin are likely physiological inhibitors, while α2-macroglobulin is not. Mol Immunol (2013) 54(3–4):415–22. 10.1016/j.molimm.2013.01.009
    1. Adinolfi M, Beck SE. Human complement C7 and C9 in fetal and newborn sera. Arch Dis Child (1975) 50(7):562–4. 10.1136/adc.50.7.562
    1. Väkevä A, Laurila P, Meri S. Co-deposition of clusterin with the complement membrane attack complex in myocardial infarction. Immunology (1993) 80(2):177–82.
    1. Dahlbäck K, Löfberg H, Alumets J, Dahlbäck B. Immunohistochemical demonstration of age-related deposition of vitronectin (S-protein of complement) and terminal complement complex on dermal elastic fibers. J Invest Dermatol (1989) 92(5):727–33. 10.1111/1523-1747.ep12721619
    1. Webb JH, Blom AM, Dahlbäck B. Vitamin K-Dependent Protein S Localizing Complement Regulator C4b-Binding Protein to the Surface of Apoptotic Cells. J Immunol (2002) 169(5):2580–6. 10.4049/jimmunol.169.5.2580
    1. Charles A Janeway J, Travers P, Walport M, Shlomchik MJ. The distribution and functions of immunoglobulin isotypes. In: Immunobiol Immune Syst Health Dis, 5th Ed New York: Garland Science; (2001).
    1. Kutteh WH, Moldoveanu Z, Prince SJ, Kulhavy R, Alonso F, Mestecky J. Biosynthesis of J-chain in human lymphoid cells producing immunoglobulins of various isotypes. Mol Immunol (1983) 20(9):967–76. 10.1016/0161-5890(83)90037-8
    1. Castro CD, Flajnik MF. Putting J Chain Back on the Map: How Might Its Expression Define Plasma Cell Development? J Immunol (2014) 193(7):3248–55. 10.4049/jimmunol.1400531
    1. Aksu G, Genel F, Koturoğlu G, Kurugöl Z, Kütükçüler N. Serum immunoglobulin (IgG, IgM, IgA) and IgG subclass concentrations in healthy children: a study using nephelometric technique. Turk J Pediatr (2006) 48(1):19–24.
    1. Seijsing J, Yu S, Frejd FY, Höiden-Guthenberg I, Gräslund T. In vivo depletion of serum IgG by an affibody molecule binding the neonatal Fc receptor. Sci Rep (2018) 8(1):5141. 10.1038/s41598-018-23481-5
    1. Vidarsson G, Dekkers G, Rispens T. IgG Subclasses and Allotypes: From Structure to Effector Functions. Front Immunol (2014) 5:520. 10.3389/fimmu.2014.00520
    1. Mankarious S, Lee M, Fischer S, Pyun KH, Ochs HD, Oxelius VA, et al. The half-lives of IgG subclasses and specific antibodies in patients with primary immunodeficiency who are receiving intravenously administered immunoglobulin. J Lab Clin Med (1988) 112(5):634–40.
    1. Morell A, Terry WD, Waldmann TA. Metabolic properties of IgG subclasses in man. J Clin Invest (1970) 49(4):673–80. 10.1172/JCI106279
    1. Fouda GG, Martinez DR, Swamy GK, Permar SR. The Impact of IgG transplacental transfer on early life immunity. ImmunoHorizons (2018) 2(1):14–25. 10.4049/immunohorizons.1700057
    1. Salimonu LS, Ladipo OA, Adeniran SO, Osukoya BO. Serum Immunoglobulin Levels in Normal, Premature and Postmature Newborns and Their Mothers. Int J Gynecol Obstet (1978) 16(2):119–23. 10.1002/j.1879-3479.1978.tb00410.x
    1. Garred P, Michaelsen TE, Aase A. The IgG subclass pattern of complement activation depends on epitope density and antibody and complement concentration. Scand J Immunol (1989) 30(3):379–82. 10.1111/j.1365-3083.1989.tb01225.x
    1. Michaelsen TE, Garred P, Aase A. Human IgG subclass pattern of inducing complement-mediated cytolysis depends on antigen concentration and to a lesser extent on epitope patchiness, antibody affinity and complement concentration. Eur J Immunol (1991) 21(1):11–6. 10.1002/eji.1830210103
    1. Naughton MA, Walport MJ, Würzner R, Carter MJ, Alexander GJ, Goldman JM, et al. Organ-specific contribution to circulating C7 levels by the bone marrow and liver in humans. Eur J Immunol (1996) Sep 26(9):2108–12. 10.1002/eji.1830260922
    1. Würzner R, Joysey VC, Lachmann PJ. Complement component C7. Assessment of in vivo synthesis after liver transplantation reveals that hepatocytes do not synthesize the majority of human C7. J Immunol (1994) 152(9):4624–9.
    1. Høgåsen AK, Würzner R, Abrahamsen TG, Dierich MP. Human polymorphonuclear leukocytes store large amounts of terminal complement components C7 and C6, which may be released on stimulation. J Immunol Baltim Md 1950 (1995) 154(9):4734–40.

Source: PubMed

3
Prenumerera