Early immune responses have long-term associations with clinical, virologic, and immunologic outcomes in patients with COVID-19.
Zicheng HuKattria van der PloegSaborni ChakrabortyPrabhu S ArunachalamDiego MoriKaren JacobsonHector BonillaJulie ParsonnetJason R AndrewsHaley HedlinLauren de la ParteKathleen DantzlerMaureen TyGene TanCatherine A BlishSaki TakahashiIsabel Rodriguez-BarraquerBryan GreenhouseAtul Janardhan ButteUpinder SinghBali PulendranTaia T WangPrasanna JagannathanPublished in: Research square (2022)
The great majority of SARS-CoV-2 infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, there is substantial heterogeneity in SARS-CoV-2-specific memory immune responses following infection. There remains a critical need to identify host immune biomarkers predictive of clinical and immunologic outcomes in SARS-CoV-2-infected patients. Leveraging longitudinal samples and data from a clinical trial in SARS-CoV-2 infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients within the first 2 weeks of symptom onset. We identify early immune signatures, including plasma RIG-I levels, early interferon signaling, and related cytokines (CXCL10, MCP1, MCP-2 and MCP-3) associated with subsequent disease progression, control of viral shedding, and the SARS-CoV-2 specific T cell and antibody response measured up to 7 months after enrollment. We found that several biomarkers for immunological outcomes are shared between individuals receiving BNT162b2 (Pfizerâ€"BioNTech) vaccine and COVID-19 patients. Finally, we demonstrate that machine learning models using 7-10 plasma protein markers measured early within the course of infection are able to accurately predict disease progression, T cell memory, and the antibody response post-infection in a second, independent dataset.
Keyphrases
- sars cov
- immune response
- respiratory syndrome coronavirus
- clinical trial
- machine learning
- dendritic cells
- single cell
- working memory
- toll like receptor
- gene expression
- type diabetes
- mass spectrometry
- dna methylation
- metabolic syndrome
- depressive symptoms
- randomized controlled trial
- open label
- small molecule
- artificial intelligence
- inflammatory response
- electronic health record
- deep learning
- genome wide
- drug induced
- preterm birth
- phase iii
- phase ii
- double blind
- sleep quality