Identification of pre-infection markers and differential plasma protein expression following SARS-CoV-2 infection in people living with HIV

Abstract

Background: Mechanisms contributing to COVID-19 severity in people with HIV (PWH) are poorly understood. We evaluated temporal changes in plasma proteins following SARS-CoV-2 infection and identified pre-infection proteomic markers associated with future COVID-19.

Methods: We leveraged data from the global Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE). Antiretroviral therapy (ART)-treated PWH with clinical, antibody-confirmed COVID-19 as of September 2021 were matched on geographic region, age, and sample timing to antibody negative controls. For cases and controls, pre COVID-19 pandemic specimens were obtained prior to January 2020 to assess change over time and relationship to COVID-19 severity, using false-discovery adjusted mixed effects modeling.

Findings: We compared 257 unique plasma proteins in 94 COVID-19 antibody-confirmed clinical cases and 113 matched antibody-negative controls, excluding COVID-19 vaccinated participants (age 50 years, 73% male). 40% of cases were characterized as mild; 60% moderate to severe. Median time from COVID-19 infection to follow-up sampling was 4 months. Temporal patterns of protein changes differed based on COVID-19 disease severity. Among those experiencing moderate to severe disease vs. controls, NOS3 increased whereas ANG, CASP-8, CD5, GZMH, GZMB, ITGB2, and KLRD1 decreased. Higher pre-pandemic levels of granzymes A, B and H (GZMA, GZMB and GZMH) were associated with the future development of moderate-severe COVID-19 and were related to immune function.

Interpretation: We identified temporal changes in proteins closely linked to inflammatory, immune, and fibrotic pathways which may relate to COVID-19-related morbidity among ART-treated PWH. Further we identified key granzyme proteins associated with future COVID-19 in PWH.

Funding: This study is supported through NIH grants U01HL123336, U01HL123336-06 and 3U01HL12336-06S3, to the clinical coordinating center, and U01HL123339, to the data coordinating center as well as funding from Kowa Pharmaceuticals, Gilead Sciences, and a grant award through ViiV Healthcare. The NIAID supported this study through grants UM1 AI068636, which supports the AIDS Clinical Trials Group (ACTG) Leadership and Operations Center, and UM1 AI106701, which supports the ACTG Laboratory Center. This work was also supported by NIAID through grant K24AI157882 to MZ. The work of IS was supported by the intramural research program of NIAID/NIH.

Keywords: COVID-19; Granzyme; Human immunodeficiency virus; SARS-CoV-2.

Fig. 1

Participant Selection diagram. Overall, 207 individuals were in our final cohort.

Fig. 2

Temporal changes in protein expression following COVID-19 infection. Each point represents the change in protein expression following COVID-19 (x axis) for a given protein and it’s corresponding -log₁₀p value (y axis). The further away a point is from the 0 value on the x axis, the larger the change in protein expression following COVID-19 as compared to controls, while the higher the point is, the smaller the p value. The dotted horizontal line indicates a nominal p = 0.05. The proteins with FDR corrected p < 0.1 are labeled and colored according to FDR corrected p values. All linear mixed models were corrected for ASCVD risk score and the time difference between the two measurements and included a random intercept per patient. Protein name abbreviations can be found in Table 1. ASCVD: atherosclerotic cardiovascular disease; COVID-19: Coronavirus disease 2019.

Fig. 3

A) Association between temporal changes in protein expression and COVID-19 severity. Each point represents the change in protein expression following COVID-19 (x axis) for a given protein and it’s corresponding -log₁₀p value (y axis). The further away a point is from the 0 value on the x axis, the larger the change in protein expression following COVID-19 as compared to controls, while the higher the point is the smaller the p value. The dotted horizontal line indicates a nominal p = 0.05. The proteins with FDR corrected p < 0.1 for coefficient are labeled and colored according to FDR corrected p values. All linear mixed models were corrected for ASCVD risk score and the time difference between the two measurements and included a random intercept per patient. B) Protein–protein interaction network of significant proteins. Nodes represent proteins showing significant differential expression following mild and/or moderate-severe COVID-19 as compared to controls in the final analytical cohort. Edges represent the confidence level of the inter-relatedness where the width is proportional to the confidence level based on all interaction sources. Panel A shows which proteins were associated with the different COVID-19 severity grades. Panel B shows the disease–gene associations of the proteins. Panel C shows the biological process gene ontology terms. C) Differential expression of proteins between mild COVID-19 and moderate-severe COVID-19 vs. control in the different stratification groups. Beta coefficients and 95% confidence intervals from linear mixed models of proteins showing significant changes in expression levels following mild and/or moderate-severe COVID-19 vs. control in the final analytical cohort and for each stratification group. All linear mixed models were corrected for ASCVD risk score and the time difference between the two measurements and included a random intercept per patient. Boxes are colored if nominal p < 0.05 and the intensity of the color represents the magnitude of the beta coefficient. Protein name abbreviations can be found in Table 1. ASCVD: atherosclerotic cardiovascular disease; COVID-19: Coronavirus disease 2019.

Fig. 4

Temporal trend plots of GZMB and GZMH levels stratified by COVID-19 severity. Spaghetti plots show the intra-individual changes in protein expression stratified by COVID-19 severity. Red lines indicate temporal regression lines for the given group. GZMB, GZMH: Granzyme B, H.

Fig. 5

Heatmap of Spearman correlation values of baseline expression levels of significant proteins in our analyses. Abbreviations can be found in Table 1.

Fig. 6

Differences in baseline protein expression between those who later acquire COVID-19 vs. controls. Each point represents the difference in baseline protein expression value (x-axis) between those who will later acquire COVID-19 and those who will not (controls), and the corresponding -log₁₀p value (y axis). The further away a point is from the 0 value on the x axis, the larger the difference in protein expression between future cases and controls, while the higher the point is the smaller the p value. The dotted horizontal line indicates a nominal p = 0.05. The proteins with FDR corrected p < 0.1 are labeled and colored according to FDR corrected p values. All linear regression models were corrected for ASCVD risk score. Protein name abbreviations can be found in Table 1. ASCVD: atherosclerotic cardiovascular disease; COVID-19: Coronavirus disease 2019. GZMA, GZMB, GZMH: Granzyme A, B, H.

Fig. 7

Differences in baseline protein expression with regards to COVID-19 severity grade. Each point represents the difference in baseline protein expression value (x-axis) between those who will later acquire COVID-19 and have mild grade disease and those who will not (controls) or moderate-severe grade disease and controls, and the corresponding -log₁₀p value (y axis). The further away a point is from the 0 value on the x axis, the larger the difference in protein expression future cases and controls, while the higher the point is the smaller the p value. The dotted horizontal line indicates a nominal p = 0.05. The proteins with FDR corrected p < 0.1 are labeled and colored according to FDR corrected p values. GZMA, B, H and are highlighted on the mild COVID-19 vs. control plot to show the difference in effect size and p values as compared to the moderate-severe group vs. controls. All linear regression models were corrected for ASCVD risk score. ASCVD: atherosclerotic cardiovascular disease; COVID-19: Coronavirus disease 2019; GZMA, GZMB, GZMH: Granzyme A, B, H.

Fig. 8

A) Correlation between baseline GZMA, GZMB and GZMH with clinical, metabolic, lipid and immunological parameters. B) Scatter plots between baseline GZMA, GZMB, GZMH and CD4, CD8 and CD4/CD8 levels. Red lines indicate regression lines with 95% confidence bounds indicated in gray between the given proteins and CD4, CD8 and CD4/CD8 levels. Spearman correlation values and corresponding p values are reported for each graph. ART: antiretroviral therapy; ASCVD: atherosclerotic cardiovascular disease; BMI: Body mass index; GZMA, GZMB, GZMH: Granzyme A, B, H; HDL: high-density lipoprotein; LDL: low density lipoprotein.