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. 2024 Jan 3;15(1):216.
doi: 10.1038/s41467-023-44090-5.

Features of acute COVID-19 associated with post-acute sequelae of SARS-CoV-2 phenotypes: results from the IMPACC study

Al Ozonoff #  1 , Naresh Doni Jayavelu #  2 , Shanshan Liu #  1 , Esther Melamed #  3 , Carly E Milliren #  1 , Jingjing Qi #  4 , Linda N Geng #  5 , Grace A McComsey  6 , Charles B Cairns  7 , Lindsey R Baden  8 , Joanna Schaenman  9 , Albert C Shaw  10 , Hady Samaha  11 , Vicki Seyfert-Margolis  12 , Florian Krammer  4 , Lindsey B Rosen  13 , Hanno Steen  8 , Caitlin Syphurs  1 , Ravi Dandekar  14 , Casey P Shannon  15 , Rafick P Sekaly  6 , Lauren I R Ehrlich  3 , David B Corry  16 , Farrah Kheradmand  16 , Mark A Atkinson  17 , Scott C Brakenridge  17 , Nelson I Agudelo Higuita  18 , Jordan P Metcalf  18 , Catherine L Hough  19 , William B Messer  19 , Bali Pulendran  5 , Kari C Nadeau  5 , Mark M Davis  5 , Ana Fernandez Sesma  4 , Viviana Simon  4 , Harm van Bakel  4 , Seunghee Kim-Schulze  4 , David A Hafler  10 , Ofer Levy  8 , Monica Kraft  20 , Chris Bime  20 , Elias K Haddad  7 , Carolyn S Calfee  14 , David J Erle  14 , Charles R Langelier  14 , Walter Eckalbar  14 , Steven E Bosinger  11 ; IMPACC Network; Bjoern Peters  21 , Steven H Kleinstein  10 , Elaine F Reed  9 , Alison D Augustine  13 , Joann Diray-Arce  1 , Holden T Maecker  5 , Matthew C Altman  2 , Ruth R Montgomery  10 , Patrice M Becker  13 , Nadine Rouphael  22
Collaborators, Affiliations

Features of acute COVID-19 associated with post-acute sequelae of SARS-CoV-2 phenotypes: results from the IMPACC study

Al Ozonoff et al. Nat Commun. .

Abstract

Post-acute sequelae of SARS-CoV-2 (PASC) is a significant public health concern. We describe Patient Reported Outcomes (PROs) on 590 participants prospectively assessed from hospital admission for COVID-19 through one year after discharge. Modeling identified 4 PRO clusters based on reported deficits (minimal, physical, mental/cognitive, and multidomain), supporting heterogenous clinical presentations in PASC, with sub-phenotypes associated with female sex and distinctive comorbidities. During the acute phase of disease, a higher respiratory SARS-CoV-2 viral burden and lower Receptor Binding Domain and Spike antibody titers were associated with both the physical predominant and the multidomain deficit clusters. A lower frequency of circulating B lymphocytes by mass cytometry (CyTOF) was observed in the multidomain deficit cluster. Circulating fibroblast growth factor 21 (FGF21) was significantly elevated in the mental/cognitive predominant and the multidomain clusters. Future efforts to link PASC to acute anti-viral host responses may help to better target treatment and prevention of PASC.

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Conflict of interest statement

M.C.A. has received grant support from NIH-R01AI32774 for this project funded through this R01 and travel fees from NIAID for travel to the American Thoracic Society 2022 to present data related to this study. M.A.A. has received funding from NIH, NIAID-5U54AI142766-03 through institution. L.R.B. has received grant support from NIH NIAID, through institution. P.M.B. and A.D.A. federal employees serving as a project scientist for this project but had no role in funding decisions or oversight of relevant grants. B.P. has received funding from NIH/NIAID. C.B.C. has received funding from NIAID with payments to institution (Drexel University), Bill & Melinda Gates Foundation for COVID-19 work paid to institution, consulting fees from bioMerieux on clinical biomarkers, serves as DSMB, Advisory board for Convalescent Plasma COVID-19 study for the National Heart, Lung and Blood Institute (NHLBI), and is acting Leadership as President Board of Directors for the National Foundation of Emergency Medicine (NFEM), a non-profit supporting emergency medicine research and researchers. C.C. has received funding from NHLBI, grants from Bayer, Roche-Genentech, Quantum Leap Healthcare Collaborative, and consulting fees from Vasomune, Gen1e Life Sciences, Cellenkos, Janssen. L.E. has received grant funding from NIH R01AI104870-S1. D.E. has received NIH grants awarded to institution (UCSF). C.L.H. has received funding from NIH and the American Lung Association, travel support from Stanford, Harvard, Critical Care Clinical Trialists, Critical Care Reviews, and the University of Michigan, serves as DSMB Quantum Health for iSPY COVID, and paid participation as member, Board of Directors for American Thoracic Society. J.P.M. has received funding from NIH Grant # 3U19AI0626629-17S2. S.H.K. has received paid consulting fees from Peraton for personal consulting related to Immport data repository. M.K. has received grants support from NIAID through institution (University of Arizona). F.K.R. has received funding from NIAID Collaborative Influenza Vaccine Innovation Centers (CIVIC) contract 75N93019C00051, JPB Foundation and the Open Philanthropy Project (research grant 2020-215611, 5384), National Cancer Institute, NIH contract no.75N91019D00024, Task order no. 75N91020F00003, research funding from Pfizer for development of animal models for SARS-CoV-2, consulting fees from Pfizer, Seqirus, Avimex, Third Rock Ventures, paid lecture fees, and patents filed at the Icahn School of Medicine at Mount Sinai relating to SARS-CoV-2 serological assays (the “Serology Assays” and NDV-based SARS-CoV-2 vaccines which list F.K.R. as co-inventor). G.A.M. has received consulting fees from Gilead. E.M. has received funding from the NIH IMPACC R01AI104870-S1, grants from Babson Diagnostics, K0826-1616-11 through Institution Dell Medical School at UT Austin, paid speaker fees from MS Association of America, and serves as DSMB for Advisory boards of Genentech, Horizon, Teva and Viela Bio. W.B.M. has received funding from NIH NIAID R01AI14583. R.R.M. has contracts and grants for IMPACC study from NIAID AI 089992 aid and a Leadership Councilor role 2018-2021 for Society of Leukocyte Biology. K.C.N. has research funding from the National Heart, Lung, and Blood Institute (NHLBI), National Institute of Environmental Health Sciences (NIEHS), Food Allergy Research & Education (FARE), Director of the World Allergy Organization center of Excellence for Stanford and National Institute of Allergy and Infectious Diseases (NIAID) through institution, paid participation for service on Data Safety Monitoring Board of Director from World Allergy Organization Center of Excellence for Stanford, earns stocks as co-founder at Seed Health, IgGenix, ClostraBio, ImmuneID and financial interests as advisor and co-founder for Cour Pharma, Before Brands, Alladapt, and Latitude, is a national scientific committee member for Network ITN, NIH clinical research centers, and has listed Patents: Mixed allergen composition and methods for using the same Granulocyte-based methods for detecting and monitoring immune system disorders, licensee: (Alladapt and Before Brands no: US15/048,609); Application number: US12/610,94 Methods and Assays for Detecting and Quantifying Pure Subpopulations of White blood cells in immune system disorders. O.L. has received NIH/NIAID grants through institution for Human Immunology Project Consortium Funding (U19) 1-U19-AI118608-01A1 as PI Role and support as a speaker for presentation regarding the Coronavirus pandemic from Midsized Bank Coalition of Americ (MBCA) and Moody’s Analytics. E.F.R. has received grants supported by NIAID U19AI12891303. N.G.R. has research grants from NIH, Pfizer, Merck, Sanofi, Quidel, and Lilly, and serves on safety committees for ICON and EMMES and the advisory boards of Moderna and Sanofi. Her institution has also received funding from NIH to conduct clinical trials of COVID-19 vaccines. J.S. received a grant from NIAID U19 for study implementation. A.C.S. has financial support from NIH U19 AI089992, NIH K24 AG042489. V.S. filed Patents at the Icahn School of Medicine at Mount Sinai relating to SARS-CoV-2 serological assays (the “Serology Assays” and NDV-based SARS-CoV-2 vaccines, which list V.S. as co-inventor. H.B. has received funding from NIH (Dengue Human Immunology Project Consortium - Mount Sinai IMPACC COVID-19 Cores), U19 AI118610 S1, NIH, CEIRR,75N93021C00014. SEB All funding sources are from NIH U19 AI090023-1S1, paid honoraria for serving on SAB for NIH NIAID P01AI174856-01, travel support from the University of Manitoba, and received TAK-242 from TAKEDA for pre-clinical testing. H.S. has received funding from 3 U19 AI 118608-05S3 through institution and travel support from NIAID. L.G. has received funding from Sean N. Parker Center for Allergy & Asthma Research, grants from Pfizer, and consulting fees from UnitedHealth Group. H.M. has received funding from NIH grant 2U19AI057229. R.D. has received grant support from UCSF COVID-19 Immunophenotyping Clinical Study and Core Laboratories (Grant number U19AI077439). V.S.M. has grants paid consulting as Vice Chair for EveryLife Foundation, Advisory board for Gemini labs, and stocks at My Own Med, Inc., d/b/a Respond Health. The remaining authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Survey completion and clustering of participant-reported outcomes after hospital discharge (N = 590).
A Upset plot depicting the number of participants completing surveys at 3 (m3), 6 (m6), 9 (m9), and 12 months (m12) after hospital discharge. B Radar plot showing relative deficit for each of four different clusters across several participant-reported outcomes: EQ-5D-5L Health Recovery Score (Health), PROMIS Cognitive Function Score (Cognitive), PROMIS Psychosocial Illness Impact Positive Score (Psychosocial), PROMIS Global Mental Health Score (Mental), PROMIS Dyspnea Score (Dyspnea), and PROMIS Physical Function Score (Physical). The radial axis denotes a t-statistic comparing the within-cluster mean to the remaining sample, with t = 0 denoting the overall sample mean and negative values denoting a deficit. The 4 clusters are: solid gray, minimal deficit (MIN); blue line, physical predominant deficit (PHY); yellow line, mental/cognitive predominant deficit (COG); and red line, multidomain deficit (MLT). PROMIS Patient-Reported Outcomes Measurement Information System.
Fig. 2
Fig. 2. Forest Plot showing adjusted odds ratios (ORs) for factors associated with patient-reported outcome (PRO) clusters with more deficits compared to minimal deficit, using multivariable multinomial logistic regression (N = 590).
A Comparison of PRO clusters PHY, COG, and MLT with PRO cluster MIN. B Comparison of PRO clusters PHY and MIN (left); clusters COG and MIN (middle); clusters MLT and MIN (right). MIN minimal deficit, PHY physical predominant deficit, COG mental/cognitive predominant deficit, MLT multidomain deficit, MV Mechanical ventilation, ECMO Extracorporeal membrane oxygenation.
Fig. 3
Fig. 3. SARS-CoV-2 viral RNA levels and antibody responses.
A N1 Ct values: shown are SARS-CoV-2 N1 gene PCR cycle threshold (Ct) values (viral loads) measured from samples collected during the first 28 days of hospital admission by four PRO clusters, minimal deficit (MIN, n = 657), physical predominant (PHY, n = 174), deficit, mental/cognitive predominant (COG, n = 172 and deficit, multidomain (MLT, n = 112). Shown are median values (horizontal lines), interquartile ranges (boxes), and 1.5 IQR (whiskers), as well as all individual points. Because lower Ct values indicate higher viral loads, the y axis is reversed. The viral loads were significantly (adj. p = 0.03) associated with the PRO clusters. B anti-RBD IgG values: Shown are anti-RBD IgG values measured from samples collected during the first 28 days of hospital admission by four PRO clusters, minimal deficit (MIN, n = 907), physical predominant (PHY, n = 221), deficit, mental/cognitive predominant (COG, n = 230) and deficit, multidomain (MLT, n = 149). Shown are median values of area under the curve (AUC) (horizontal lines), interquartile ranges (boxes), and 1.5 IQR (whiskers), as well as all individual points. The titers were significantly (adj. p = 0.014) associated with the PRO clusters. C Ratio of anti-RBD IgG to N1 values: shown are scaled ratio of anti-RBD IgG to SARS-CoV-2 viral loads (N1 gene) values from samples collected during the first 28 days of hospital admission by four PRO clusters, minimal deficit (MIN, n = 560), physical predominant (PHY, n = 156), deficit, mental/cognitive predominant (COG, n = 141) and deficit, multidomain (MLT, n = 99). Shown are median values (horizontal lines), interquartile ranges (boxes), and 1.5 IQR (whiskers), as well as all individual points. The ratio of titers to viral loads was also significantly (adj. p = 0.05) associated with the PRO clusters. The four PRO clusters are the following in gray: minimal deficit (MIN), in blue: deficit, physical predominant (PHY), in yellow: deficit, mental/cognitive predominant (COG), and in red: deficit, multidomain (MLT). The lines and asterisks on top of the figure denote pairwise statistical significance, *p < 0.05, **p < 0.01, ***p < 0.001. Statistical differences were determined from generalized linear mixed effects models adjusting for age, sex, participant, and enrollment site. P values were adjusted using the Benjamini-Hochberg method to account for multiple comparisons. See Methods for more details.
Fig. 4
Fig. 4. B cell to non-granulocyte frequency.
Shown are B cell to non-granulocyte frequency values from samples collected during the first 28 days of hospital admission by four PRO clusters, minimal deficit (MIN, n = 584), physical predominant (PHY, n = 140), deficit, mental/cognitive predominant (COG, n = 145) and deficit, multidomain (MLT, n = 107). Shown are median values (horizontal lines), interquartile ranges (boxes), and 1.5 IQR (whiskers), as well as all individual points. The repeated-measurement model identified significant differences of B cell to non-granulocyte frequency in association with convalescent clusters (adj. p = 0.0191). The 4 clusters are the following in gray: minimal deficit (MIN), in blue: deficit, physical predominant (PHY), in yellow: deficit, mental/cognitive predominant (COG), and in red: deficit, multidomain (MLT). The lines and asterisks on top of the figure denote pairwise statistical significance, *p < 0.05, **p < 0.01, ***p < 0.001. Statistical differences were determined from generalized linear mixed effects models adjusting for age, sex, participant, and enrollment site. P values were adjusted using the Benjamini–Hochberg method to account for multiple comparisons. See Methods for more details.
Fig. 5
Fig. 5. Circulating fibroblast growth factor 21 expression.
Circulating fibroblast growth factor 21 (FGF21) NPX (Normalized protein expression): Shown are FGF21 NPX values from samples collected during the first 28 days of hospital admission by four PRO clusters, minimal deficit (MIN, n = 716), physical predominant (PHY, n = 189), deficit, mental/cognitive predominant (COG, n = 210) and deficit, multidomain (MLT, n = 139). Shown are median values (horizontal lines), interquartile ranges (boxes), and 1.5 IQR (whiskers), as well as all individual points. The generalized additive model (GAM) identified a significant difference in FGF21 expression level in association with convalescent cluster groups (adj. p = 0.0135). The four clusters are the following in gray: minimal deficit (MIN), in blue: deficit, physical predominant (PHY), in yellow: deficit, mental/cognitive predominant (COG), and in red: deficit, multidomain (MLT). Statistical differences were determined from generalized linear mixed effects models adjusting for age, sex, participant, and enrollment site. P values were adjusted using the Benjamini–Hochberg method to account for multiple comparisons. See Methods for more details.
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