Serum Biomarkers Predict Symptom Duration in Long Term COVID-19 Across a Diverse Population (preprint)

Background: Prolonged symptoms after SARS-CoV-2 infection are well-documented. However, which factors influence development of long-term symptoms, how symptoms vary across ethnic groups, and whether long-term symptoms correlate with serologic biomarkers remain elusive. Methods: Adult inpatient and outpatient SARS-CoV-2 RT-PCR positive patients were recruited at Stanford from March 2020 to February 2021. Study participants were seen for in-person visits at diagnosis and every 1-3 months for up to one year after diagnosis; they completed symptom surveys and underwent sampling procedures (blood draw and nasal swab) at each visit. Findings: Our cohort (n=617) ranged from asymptomatic to critical COVID-19 infections. 40% of participants reported at least one symptom associated with COVID-19 six months after diagnosis. Median time from diagnosis to first resolution of all symptoms was 44 days, median time from diagnosis to sustained symptom resolution with no recurring symptoms for one month or longer was 214 days. Serum anti-nucleocapsid IgG level in the first week of infection was predictive of time to symptom resolution. A prior diagnosis of lung disease was associated with longer time to symptom resolution. COVID-19 disease severity, ethnicity, sex, cytomegalovirus (CMV) seropositivity, and remdesivir use did not affect time to sustained symptom resolution. More than 90% of participants had SARS-CoV-2-specific antibody>1000 AU/mL nine months after diagnosis. Interpretation: Our findings showed that all disease severities had a similar risk of developing post-COVID-19 syndrome in an ethnically diverse population. Comorbid lung disease and lower levels of initial IgG response to SARS-CoV-2 nucleocapsid antigen were associated with longer symptom duration. Trial Registration: National clinical trial database NCT04664309.Funding: NIH CTSA grant, U54 NIH Grant, R21 NIEHS, Sean N Parker Center for Allergy and Asthma Research at Stanford University, the Sunshine Foundation, the Crown Foundation, and the Parker Foundation.Declaration of Interest: Dr. Boyd received support for the current manuscript from Meso Scale Discovery and NIH; 418 received consulting fees by Regeneron for expert testimony, has stocks or stock options in 419 AbCellera Biologics; Dr. Chinthrajah reports grants from NIAID, CoFAR, Aimmune, DBV 420 Technologies, Astellas, Regeneron, Stanford Maternal and Child Health Research Institute 421 (MCHRI), and FARE. She is an Advisory Board Member at Alladapt Therapeutics, Novartis, 422 Genentech, Sanofi, Allergenis, and Nutricia; Dr. Manisha Desai received support from Chan 423 Zuckerberg Foundation; Dr. Maecker received grants or contracts from NIH, Bill & Melinda 424 Gates Foundation, Ionis Corporation, Amgen Corporation; Consulting fees from Magarray Corp; 425 payment or honoraria from UCLA, UC Davis; leadership or fiduciary role at Cytek SAB; stocks 426 or stock options at BD Biosciences; Dr. Nadeau reports grants from National Institute of Allergy and Infectious Diseases (NIAID), National Heart, Lung, and Blood Institute (NHLBI), National Institute of Environmental Health Sciences (NIEHS), and Food Allergy Research & Education (FARE); Director of World Allergy Organization (WAO) , Advisor at Cour Pharma, Consultant for Excellergy, Red tree ventures, and Phylaxis, Co-founder of Before Brands, Alladapt, Latitude, and IgGenix; and National Scientific Committee member at Immune Tolerance Network (ITN), and National Institutes of Health (NIH) clinical research centers, outside the submitted work; patents include, “Mixed allergen composition and methods for using the same”, “Granulocyte-based methods for detecting and monitoring immune system disorders”, “Methods and Assays for Detecting and Quantifying Pure Subpopulations of White Blood Cells in Immune System Disorders,” and “Methods of isolating allergen-specific antibodies from humans and uses thereof”; Dr. Benjamin Pinsky received grants or contracts for the present manuscript from MesoScale Diagnostics; Dr. Angele Rogers was a Clinical Trials Advisory Board Member for Merck; Dr. Sindher reports support for the present manuscript from the NIH, Regeneron, DBV Technologies, Aimmune, Novartis, CoFAR, FARE, participated on a DSMB for Astra Zeneca, DBV, and received payment or honorarium from FARE; Neera Ahuja, Maja Artandi, Linda Barman, Catherine Blish, Andra Blomkalns, William Collins, MacKenzie Cox, Linda Geng, Xiaolin Jia, Megan Mahoney, Monali Manohar, Ruth O’hara, Rajan Puri, Katharina Roltgen, Laura Vaughan, Samuel Yang, Shu Cao, Iris Chang, Hena Din, Evan Do, Andrea Fernandez, Alexandra Lee, Natasha Purington, Yael Rosenberg-Hasson, Theo Snow, Daniel Solis, Michelle Verghese, and Yingjie Weng have no conflict of interest.Ethical Approval: This study was reviewed and approved by the Stanford Administrative Panel on Human Subjects in Medical Research.

Asthma phenotypes, associated comorbidities, and long-term symptoms in COVID-19 (preprint)

Background: It is unclear if asthma and its allergic phenotype are risk factors for hospitalization or severe disease from SARS-CoV-2. Methods: All patients testing positive for SARS-CoV-2 between March 1 and September 30, 2020, were retrospectively identified and characterized through electronic analysis at Stanford. A sub-cohort was followed prospectively to evaluate long-term COVID-19 symptoms. Results: 168,190 patients underwent SARS-CoV-2 testing, and 6,976 (4·15%) tested positive. In a multivariate analysis, asthma was not an independent risk factor for hospitalization (OR 1·12 [95% CI 0·86, 1·45], p=0·40). Among SARS-CoV-2 positive asthmatics, allergic asthma lowered the risk of hospitalization and had a protective effect compared to non-allergic asthma (OR 0·52 (0·28, 0·91), p=0·026); there was no association between baseline medication use as characterized by GINA and hospitalization risk. Patients with severe COVID-19 disease had lower eosinophil levels during hospitalization compared to patients with mild or asymptomatic disease, independent of asthma status (p=0.0014). In a patient sub-cohort followed longitudinally, asthmatics and non-asthmatics had similar time to resolution of COVID-19 symptoms, particularly lower respiratory symptoms. Conclusions: Asthma is not a risk factor for more severe COVID-19 disease. Allergic asthmatics were half as likely to be hospitalized with COVID-19 compared to non-allergic asthmatics. Lower levels of eosinophil counts (allergic biomarkers) were associated with more severe COVID-19 disease trajectory. Recovery was similar among asthmatics and non-asthmatics with over 50% of patients reporting ongoing lower respiratory symptoms three months post-infection.

New-Onset IgG Autoantibodies in Hospitalized Patients with COVID-19 (preprint)

Coronavirus Disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. We developed three different protein arrays to measure hallmark IgG autoantibodies associated with Connective Tissue Diseases (CTDs), Anti-Cytokine Antibodies (ACA), and anti-viral antibody responses in 147 hospitalized COVID-19 patients in three different centers. Autoantibodies were identified in approximately 50% of patients, but in <15% of healthy controls. When present, autoantibodies largely targeted autoantigens associated with rare disorders such as myositis, systemic sclerosis and CTD overlap syndromes. Anti-nuclear antibodies (ANA) were observed in ~25% of patients. Patients with autoantibodies tended to demonstrate one or a few specificities whereas ACA were even more prevalent, and patients often had antibodies to multiple cytokines. Rare patients were identified with IgG antibodies against angiotensin converting enzyme-2 (ACE-2). A subset of autoantibodies and ACA developed de novo following SARS-CoV-2 infection while others were transient. Autoantibodies tracked with longitudinal development of IgG antibodies that recognized SARS-CoV-2 structural proteins such as S1, S2, M, N and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. COVID-19 patients with one or more autoantibodies tended to have higher levels of antibodies against SARS-CoV-2 Nonstructural Protein 1 (NSP1) and Methyltransferase (ME). We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.