Abstract
Age is a significant risk factor for the coronavirus disease 2019 (COVID-19) severity due to immunosenescence and certain age-dependent medical conditions (e.g., obesity, cardiovascular disorder, and chronic respiratory disease). However, despite the well-known influence of age on autoantibody biology in health and disease, its impact on the risk of developing severe COVID-19 remains poorly explored. Here, we performed a cross-sectional study of autoantibodies directed against 58 targets associated with autoimmune diseases in 159 individuals with different COVID-19 severity (71 mild, 61 moderate, and 27 with severe symptoms) and 73 healthy controls. We found that the natural production of autoantibodies increases with age and is exacerbated by SARS-CoV-2 infection, mostly in severe COVID-19 patients. Multiple linear regression analysis showed that severe COVID-19 patients have a significant age-associated increase of autoantibody levels against 16 targets (e.g., amyloid β peptide, β catenin, cardiolipin, claudin, enteric nerve, fibulin, insulin receptor a, and platelet glycoprotein). Principal component analysis with spectrum decomposition and hierarchical clustering analysis based on these autoantibodies indicated an age-dependent stratification of severe COVID-19 patients. Random forest analysis ranked autoantibodies targeting cardiolipin, claudin, and platelet glycoprotein as the three most crucial autoantibodies for the stratification of severe COVID-19 patients ≥50 years of age. Follow-up analysis using binomial logistic regression found that anti-cardiolipin and anti-platelet glycoprotein autoantibodies significantly increased the likelihood of developing a severe COVID-19 phenotype with aging. These findings provide key insights to explain why aging increases the chance of developing more severe COVID-19 phenotypes.
| Original language | English |
|---|---|
| Article number | 21 |
| Journal | npj Aging |
| Volume | 9 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 12.2023 |
Funding
We acknowledge the patients for participating in this study. We would like to recognize the contributions of Lev Rochel Bikur Cholim of Lakewood (led by Rabbi Yehuda Kasirer and Mrs. Leeba Prager) and the hundreds of volunteers who collected samples for this research through the MITZVA Cohort. We thank Immunosciences and Cyrex Laboratories for financial support and INOVA Diagnostics for providing their diagnostic ELISA kits for autoimmunity at a significantly discounted rate. Furthermore, we would like to thank Vilma Samayoa, David Cisneros, Roberto Melgar, Dana Ashley Hill, and Amanda Thornton for their technical assistance. We thank the São Paulo Research Foundation (FAPESP grants 2018/18886-9, 2020/01688-0, and 2020/07069-0 to O.C.-M., 2020/16246-2 to D.L.M.F., 2020/09146-1 to P.P.F., 2020/07972-1 to G.C.B., 2020/11710-2 to DRP) for financial support. FAPESP and CAPES supported computational analysis. We acknowledge the National Council for Scientific and Technological Development (CNPq) Brazil (grants: 309482/2022-4 to O.C.-M. and 102430/2022-5 to L.F.S.). In addition, the contributions by G.M. and R.C. were made possible by funding from the German Federal Ministry for Education and Research (BMBF) and German Research Foundation (DFG; projects #394046635, subproject A03, as part of CRC 1365, and EXPAND-PD; CA2816/1-1) through the Berlin Institute of Health (BIH)-Center for Regenerative Therapies (BCRT) and the Berlin-Brandenburg School for Regenerative Therapies (BSRT, GSC203), respectively, and in part by the European Union’s Horizon 2020 Research and Innovation Program under grant agreements No 733006 (PACE) and 779293 (HIPGEN). We acknowledge the patients for participating in this study. We would like to recognize the contributions of Lev Rochel Bikur Cholim of Lakewood (led by Rabbi Yehuda Kasirer and Mrs. Leeba Prager) and the hundreds of volunteers who collected samples for this research through the MITZVA Cohort. We thank Immunosciences and Cyrex Laboratories for financial support and INOVA Diagnostics for providing their diagnostic ELISA kits for autoimmunity at a significantly discounted rate. Furthermore, we would like to thank Vilma Samayoa, David Cisneros, Roberto Melgar, Dana Ashley Hill, and Amanda Thornton for their technical assistance. We thank the São Paulo Research Foundation (FAPESP grants 2018/18886-9, 2020/01688-0, and 2020/07069-0 to O.C.-M., 2020/16246-2 to D.L.M.F., 2020/09146-1 to P.P.F., 2020/07972-1 to G.C.B., 2020/11710-2 to DRP) for financial support. FAPESP and CAPES supported computational analysis. We acknowledge the National Council for Scientific and Technological Development (CNPq) Brazil (grants: 309482/2022-4 to O.C.-M. and 102430/2022-5 to L.F.S.). In addition, the contributions by G.M. and R.C. were made possible by funding from the German Federal Ministry for Education and Research (BMBF) and German Research Foundation (DFG; projects #394046635, subproject A03, as part of CRC 1365, and EXPAND-PD; CA2816/1-1) through the Berlin Institute of Health (BIH)-Center for Regenerative Therapies (BCRT) and the Berlin-Brandenburg School for Regenerative Therapies (BSRT, GSC203), respectively, and in part by the European Union’s Horizon 2020 Research and Innovation Program under grant agreements No 733006 (PACE) and 779293 (HIPGEN).
Research Areas and Centers
- Academic Focus: Center for Infection and Inflammation Research (ZIEL)
DFG Research Classification Scheme
- 2.21-05 Immunology
- 2.22-18 Rheumatology
Coronavirus related work
- Research on SARS-CoV-2 / COVID-19
