SARS-CoV-2 infection and persistence in the human body and brain at autopsy

Abstract

Coronavirus disease 2019 (COVID-19) is known to cause multi-organ dysfunction1-3 during acute infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with some patients experiencing prolonged symptoms, termed post-acute sequelae of SARS-CoV-2 (refs. 4,5). However, the burden of infection outside the respiratory tract and time to viral clearance are not well characterized, particularly in the brain3,6-14. Here we carried out complete autopsies on 44 patients who died with COVID-19, with extensive sampling of the central nervous system in 11 of these patients, to map and quantify the distribution, replication and cell-type specificity of SARS-CoV-2 across the human body, including the brain, from acute infection to more than seven months following symptom onset. We show that SARS-CoV-2 is widely distributed, predominantly among patients who died with severe COVID-19, and that virus replication is present in multiple respiratory and non-respiratory tissues, including the brain, early in infection. Further, we detected persistent SARS-CoV-2 RNA in multiple anatomic sites, including throughout the brain, as late as 230 days following symptom onset in one case. Despite extensive distribution of SARS-CoV-2 RNA throughout the body, we observed little evidence of inflammation or direct viral cytopathology outside the respiratory tract. Our data indicate that in some patients SARS-CoV-2 can cause systemic infection and persist in the body for months.

Conflict of interest statement

The authors declare no competing interests.

© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

Figures

Fig. 1. Distribution, quantification and replication of SARS-CoV-2 across the human body and brain.

The heat map depicts the highest mean quantification of SARS-CoV-2 RNA (N) through ddPCR present in the autopsy tissues of 11 patients who died with COVID-19 and underwent whole-body and brain sampling. Patients are aligned from shortest to longest duration of illness (DOI) before death, listed at the bottom of the figure, and grouped into early (≤14 days), mid (15–30 days) and late (≥31 days) duration of illness. Tissues are organized by tissue group beginning with the respiratory tissues at the top and CNS at the bottom. Viral RNA levels range from 0.002 to 500,000 N gene copies per nanogram of RNA input, depicted as a gradient from dark blue at the lowest level to dark red at the highest level. Tissues that were also positive for subgenomic RNA (sgRNA+) through real-time RT–qPCR are shaded with black vertical bars. O, other; PNS, peripheral nervous system; SM, skeletal muscle.

Fig. 2. RNA in situ (RNAscope) detection of SARS-CoV-2 in extrapulmonary tissues.

a–h, SARS-CoV-2 virus is localized to the Golgi and endoplasmic reticulum, perinuclear in appearance, in the following organs and cell types (×500 magnifications, scale bars, 2 μm, all panels): thyroid of P19, demonstrating the presence of virus in follicular cells (a), oesophagus of P18, demonstrating the presence of virus in the stratified squamous epithelium (asterisk), as well as signal in capillaries within the stroma (hash) (b), spleen of P19, demonstrating the presence of virus in mononuclear leukocytes in the white pulp (c), appendix of P19, demonstrating the presence of virus in both colonic epithelium (asterisk) and mononuclear leukocytes in the stroma (hash) (d), adrenal gland of P19, demonstrating the presence of virus in endocrine secretory cells (e), ovary of P18, demonstrating the presence of virus in stromal cells of the ovary in a post-menopausal ovary (f), testis of P20, demonstrating the presence of virus in both Sertoli cells (asterisk) and maturing germ cells in the seminiferous tubules of the testis (hash) (g), endometrium of P35, demonstrating the presence of virus in endometrial gland epithelium (asterisk) and stromal cells (hash), in a pre-menopausal endometrial sample (h). The images are exemplars of extrapulmonary tissues that were positive for SARS-CoV-2 N RNA during 20 batches of ISH staining.

Fig. 3. SARS-CoV-2 protein and RNA expression in human CNS tissues.

a, High-magnification visualization of hypothalamus from P38 labelled for SARS-CoV-2 N protein (green) and neuronal nuclear (NeuN) protein (magenta), demonstrating viral-specific protein expression in neurons (white arrowheads) by IF. The z-stack orthogonal views to the right and bottom of a demonstrate NeuN labelling in the nucleus and SARS-CoV-2 protein in the cytoplasm of the cell (red arrowhead). b–d, SARS-CoV-2 spike (S) (b) and N (c) RNA (brown) by ISH and SARS-CoV-2 N (d) protein (brown) by chromogenic IHC of hypothalamus of P38. e, Infected neurons were found in the cervical spinal cord of P42 by IF, for which white arrowheads indicate NeuN-positive neurons with associated virus protein. Viral protein labelling was also identified in linear structures radiating away from neuronal cell bodies suggestive of neuronal projections (yellow arrowheads). f, A higher magnification of neuron-associated viral protein labelling. g, Viral protein was also detected by IF in neurons of the spinal ganglia at the level of the cervical spinal cord of P42 (white arrowheads). h–j, SARS-CoV-2 S (h) and N (i) RNA by ISH and SARS-CoV-2 N (j) protein by chromogenic IHC of cervical spinal cord of P42. k–m, SARS-CoV-2 S (k) and N (l) RNA by ISH and SARS-CoV-2 N (m) protein by chromogenic IHC, all of which are predominantly found in the granular layer (GL) as compared to the molecular level (ML) of cerebellum of P38. WM, white matter. n,o, SARS-CoV-2 S (n) and N (o) RNA by ISH and SARS-CoV-2 N (p) viral protein by chromogenic IHC of basal ganglia of P40. Hoechst 33342 was used to identify nuclei (blue) in all IF images, and IF images were obtained by confocal microscopy. Haematoxylin was used as a counterstain and all ISH and chromogenic IHC images were obtained by bright-field microscopy. Scale bars, 15 μm (a), 10 μm (b–d,g–p) and 25 μm (e,f).

Extended Data Fig. 1. Autopsy procurement relative to Maryland COVID-19 cases, March 19th, 2020 to March 9th, 2021.

Daily COVID-19 reported cases for Maryland (light blue bars) with 7-day average (dark blue line) with timing of autopsies (red arrows).

Extended Data Fig. 2. Analysis of ddPCR quantification.

(a) Linear mixed model analysis of estimated difference in log10ddPCR SARS-CoV-2 N copies/ng RNA between all respiratory and all non-respiratory tissues among early, mid, and late cases with SE and p-values from relevant contrasts, (b) graph of linear mixed model analysis comparing linear trends of log10ddPCR SARS-CoV-2 N copies/ng RNA by log10DOI of respiratory and non-respiratory tissues, (c) linear mixed model analysis estimating the linear trends of log10ddPCR SARS-CoV-2 N copies/ng RNA by log10DOI of individual tissue groups with intercept with standard error (SE), and slope with SE and p-values from relevant contrasts (a signification p-value indicates a non-zero slope), (d) Spearman correlation between ddPCR (N copies/ng RNA) and sgRNA (copies/µL RNA) for all tissues tested for sgRNA, with subset analyses of these tissues from early, mid and late cases and all non-respiratory and respiratory samples with 95% confidence intervals (CI), (e) Spearman correlation between ddPCR (N copies/ng RNA) and sgRNA (copies/µL RNA) for tissues jointly positive by both assays, with subset analyses of these tissues from early, mid, and late cases and all non-respiratory and respiratory samples with 95% CI, (f) receiver operating characteristic (ROC) curve of logistic regression using log10ddPCR in tissues to predict the detection of sgRNA in tissues, area under the curve is 0.965 (95% CI 0.953, 0.977), optimal cut-off for ddPCR is 1.47 N copies/ng RNA (sensitivity 93.0%, specificity 91.6%). All p-values were two-sided without adjustment for multiple comparisons.

Extended Data Fig. 3. Virus isolation summary and correlation between ddPCR and sgRNA.

(a) Summary of 55 tissues selected for virus isolation organized by the sgRNA qPCR quantification cycle (Cq) for the RNAlater preserved tissue, (b) Receiver operating characteristic (ROC) curve of logistic regression using log10ddPCR to predict the presence of cytopathic effect (CPE), area under the curve 0.887 (95% CI 0.795, 0.978), optimal cut-off for ddPCR is 758 N copies/ng RNA (sensitivity 76%, specificity 90%), (c) ROC curve of logistic regression using log10sgRNA to predict presence of CPE, area under the curve 0.915 (95% CI 0.843, 0.987), optimal cut-off for sgRNA is 25,069 copies/µL RNA (sensitivity 72%, specificity 100%). sgRNA qPCR was additionally performed on the flash frozen tissue homogenate and the supernatant from the least diluted tissue culture wells with CPE in order to rule out CPE from other causes; if both wells at that dilution showed CPE the samples were pooled.

Extended Data Fig. 4. Analysis of SARS-CoV-2 genetic diversity across body compartments in patients.

(a) P18, (b) P19, (c) P27, (d) P33, (e) P36, (f) P38. Haplotype diagrams (left) show SARS-CoV-2 spike single genome sequences detected in multiple organs. Spike NH2-terminal domain (NTD), receptor-binding domain (RBD), and furin cleavage site (F) regions are shaded grey, and remaining regions of the spike are shaded white. Ticks with different colors indicate mutations relative to the WA-1 reference sequence; green indicates non-synonymous differences from WA-1 detected in all sequences in the individual; blue indicates synonymous mutations detected variably within the individual, and pink indicates non-synonymous mutations detected variably within the individual. Bar graphs (right) show the percentage of all single genome sequences in the sample matching each haplotype. The spike region of the consensus sequence generated from short read, whole genome sequencing (WGS) of the supernatant of P38 thalamus frozen tissue on Vero E6-TMPRSS2-T2A-ACE2 cells is additional shown at the bottom of (f) for comparison.

Extended Data Fig. 5. Representative histopathologic findings in COVID-19 autopsy patients.

(a) Lung, Subject P22, exudative phase diffuse alveolar damage with hyaline membranes and mild interstitial inflammation (H&E, 100x), (b) Lung, Subject P26, proliferative phase diffuse alveolar damage and sparse inflammation (H&E, 200x), (c) Lung, Subject P22, organizing thrombus in medium sized pulmonary artery (H&E, 40x), (d) Lung, Subject P28. Diffuse pulmonary hemorrhage (H&E, 100x), (e) Heart, Subject P3, active lymphocytic myocarditis with cardiomyocyte necrosis (H&E, 400x), (f) Heart, Subject P38, microscopic focus of bland myocardial contraction band necrosis (H&E, 400x), (g) Liver, Subject P41, steatohepatitis with mild steatosis and scattered ballooned hepatocytes (H&E, 400x), (h) Liver, Subject P41, focal bridging fibrosis involving central hepatic veins (Masson trichrome, 40x), (i) Kidney, Subject P16, nodular glomerulosclerosis (Masson trichrome, 600x), (j) Spleen, Subject P16, preservation of white pulp and congestion (H&E, 40x), (k) Spleen, Subject P14, lymphoid depletion of white pulp with proteinaceous material and red pulp congestion (H&E, 100x), (l) Spleen, Subject P34, relative preservation of white pulp with extramedullary hematopoiesis (inset) in red pulp (H&E, 200x), (m) Lymph node, Subject P25, follicular hyperplasia with well-defined follicles (H&E), (n) Lymph node, Subject P25, marked plasmacytosis in the medullary cord (H&E, 400x), (o) Lymph node, Subject P25, marked plasmacytosis and sinus histiocytosis (H&E, 400x), (p) Brain, Subject P35, focal subarachnoid and intraparenchymal hemorrhage (H&E, 40x), (q) Brain, Subject P44, vascular congestion (H&E, 40x), (r) Brain, Subject P43, intravascular platelet aggregates (anti-CD61 stain, 100x). All H&E (and Masson trichrome) photomicrographs are exemplars of histopathology observed across a diversity of patients within the cohort, see Extended Data Table 4 for a summary of histopathology observed across the autopsy cohort and Supplemental data 2b for individual case-level data. The histopathologic observations were validated by a minimum of two board certified anatomic pathologist.

Extended Data Fig. 6. Temporal association of diffuse alveolar damage in patients dying from COVID-19.

Number of autopsy cases with diagnosed phase of diffuse alveolar damage (DAD) via histopathologic analysis by duration of illness. Early time points mainly show the initial exudative phase of diffuse alveolar damage, while patients dying after prolonged illness are more likely to have proliferative or fibrosing phases of DAD.