Robust SARS-CoV-2-specific and heterologous immune responses after natural infection in elderly residents of Long-Term Care Facilities

medRxiv(2021)

引用 0|浏览9
暂无评分
摘要
Long term care facilities (LTCF) provide residential and/or nursing care support for frail and elderly people and many have suffered from a high prevalence of SARS-CoV-2 infection. Although mortality rates have been high in LTCF residents there is little information regarding the features of SARS-CoV-2-specific immunity after infection in this setting or how this may influence immunity to other infections. We studied humoral and cellular immunity against SARS-CoV-2 in 152 LTCF staff and 124 residents over a prospective 4-month period shortly after the first wave of infection and related viral serostatus to heterologous immunity to other respiratory viruses and systemic inflammatory markers. LTCF residents developed high levels of antibodies against spike protein and RBD domain which were stable over 4 months of follow up. Nucleocapsid-specific responses were also elevated in elderly donors but showed waning across all populations. Antibodies showed stable and equivalent levels of functional inhibition against spike-ACE2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or RSV. SARS-CoV-2-specific cellular responses were equivalent across the life course but virus-specific populations showed elevated levels of activation in older donors. LTCF residents who are survivors of SARS-CoV-2 infection thus show robust and stable immunity which does not impact responses to other seasonal viruses. These findings augur well for relative protection of LTCF residents to re-infection. Furthermore, they underlie the potent influence of previous infection on the immune response to Covid-19 vaccine which may prove to be an important determinant of future vaccine strategy.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要