tetano
Editor, Senior Moderator
Nat Biomed Eng
. 2020 Sep 18.
doi: 10.1038/s41551-020-00611-x. Online ahead of print.
Ultrasensitive high-resolution profiling of early seroconversion in patients with COVID-19
Maia Norman[SUP] 1 2 3 [/SUP], Tal Gilboa[SUP] 1 2 4 [/SUP], Alana F Ogata[SUP] 1 2 4 [/SUP], Adam M Maley[SUP] 1 2 4 [/SUP], Limor Cohen[SUP] 1 2 5 [/SUP], Evan L Busch[SUP] 6 [/SUP], Roey Lazarovits[SUP] 1 2 4 [/SUP], Chih-Ping Mao[SUP] 1 4 [/SUP], Yongfei Cai[SUP] 7 [/SUP], Jun Zhang[SUP] 7 [/SUP], Jared E Feldman[SUP] 8 [/SUP], Blake M Hauser[SUP] 8 [/SUP], Timothy M Caradonna[SUP] 8 [/SUP], Bing Chen[SUP] 7 9 [/SUP], Aaron G Schmidt[SUP] 8 10 [/SUP], Galit Alter[SUP] 8 [/SUP], Richelle C Charles[SUP] 11 12 [/SUP], Edward T Ryan[SUP] 11 12 13 [/SUP], David R Walt[SUP] 14 15 16 [/SUP]
Affiliations
Abstract
Sensitive assays are essential for the accurate identification of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we report a multiplexed assay for the fluorescence-based detection of seroconversion in infected individuals from less than 1 ?l of blood, and as early as the day of the first positive nucleic acid test after symptom onset. The assay uses dye-encoded antigen-coated beads to quantify the levels of immunoglobulin G (IgG), IgM and IgA antibodies against four SARS-CoV-2 antigens. A logistic regression model trained using samples collected during the pandemic and samples collected from healthy individuals and patients with respiratory infections before the first outbreak of coronavirus disease 2019 (COVID-19) was 99% accurate in the detection of seroconversion in a blinded validation cohort of samples collected before the pandemic and from patients with COVID-19 five or more days after a positive nasopharyngeal test by PCR with reverse transcription. The high-throughput serological profiling of patients with COVID-19 allows for the interrogation of interactions between antibody isotypes and viral proteins, and should help us to understand the heterogeneity of clinical presentations.
. 2020 Sep 18.
doi: 10.1038/s41551-020-00611-x. Online ahead of print.
Ultrasensitive high-resolution profiling of early seroconversion in patients with COVID-19
Maia Norman[SUP] 1 2 3 [/SUP], Tal Gilboa[SUP] 1 2 4 [/SUP], Alana F Ogata[SUP] 1 2 4 [/SUP], Adam M Maley[SUP] 1 2 4 [/SUP], Limor Cohen[SUP] 1 2 5 [/SUP], Evan L Busch[SUP] 6 [/SUP], Roey Lazarovits[SUP] 1 2 4 [/SUP], Chih-Ping Mao[SUP] 1 4 [/SUP], Yongfei Cai[SUP] 7 [/SUP], Jun Zhang[SUP] 7 [/SUP], Jared E Feldman[SUP] 8 [/SUP], Blake M Hauser[SUP] 8 [/SUP], Timothy M Caradonna[SUP] 8 [/SUP], Bing Chen[SUP] 7 9 [/SUP], Aaron G Schmidt[SUP] 8 10 [/SUP], Galit Alter[SUP] 8 [/SUP], Richelle C Charles[SUP] 11 12 [/SUP], Edward T Ryan[SUP] 11 12 13 [/SUP], David R Walt[SUP] 14 15 16 [/SUP]
Affiliations
- PMID: 32948854
- DOI: 10.1038/s41551-020-00611-x
Abstract
Sensitive assays are essential for the accurate identification of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we report a multiplexed assay for the fluorescence-based detection of seroconversion in infected individuals from less than 1 ?l of blood, and as early as the day of the first positive nucleic acid test after symptom onset. The assay uses dye-encoded antigen-coated beads to quantify the levels of immunoglobulin G (IgG), IgM and IgA antibodies against four SARS-CoV-2 antigens. A logistic regression model trained using samples collected during the pandemic and samples collected from healthy individuals and patients with respiratory infections before the first outbreak of coronavirus disease 2019 (COVID-19) was 99% accurate in the detection of seroconversion in a blinded validation cohort of samples collected before the pandemic and from patients with COVID-19 five or more days after a positive nasopharyngeal test by PCR with reverse transcription. The high-throughput serological profiling of patients with COVID-19 allows for the interrogation of interactions between antibody isotypes and viral proteins, and should help us to understand the heterogeneity of clinical presentations.