Research ArticleCORONAVIRUS

JAK inhibition reduces SARS-CoV-2 liver infectivity and modulates inflammatory responses to reduce morbidity and mortality

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Science Advances  01 Jan 2021:
Vol. 7, no. 1, eabe4724
DOI: 10.1126/sciadv.abe4724
  • Fig. 1 CONSORT flow diagram for University of Pisa and Albacete Hospital cohorts.

    PS, propensity score.

  • Fig. 2 Kaplan-Meier analysis of the propensity score–matched cohorts from Pisa University and Albacete Hospital cohorts.

  • Fig. 3 Baricitinib inhibits cytokine-mediated increased infectivity of SARS-CoV-2 in organotypic primary human liver culture.

    (A) Immunofluorescence confocal imaging of a liver spheroid 48 hours after infection with SARS-CoV-2. Viral spike protein is shown in red, ACE2 in green, and DAPI (4′,6-diamidino-2-phenylindole) in blue. Arrows indicate examples of where spike protein and ACE2 signals are in close proximity. (B) Liver spheroids were treated with different cytokines (10 ng/ml), and the fold increase in ACE2 transcript levels are shown relative to controls (indicated by the solid line). Note that IFN-α2 and IFN-β significantly induce ACE2 levels. N = 2 technical replicates. (C) Combinatorial cytokine exposure does not result in increased ACE2 induction compared to IFN-α2 alone. “Other cytokines” corresponds to IFN-β, IFN-γ, TNFα, IL-1β, IL-6, IL-10, and IL-18. (D) IFN-α2 increases viral load in hepatocyte spheroids, and this effect is fully inhibited by baricitinib. N = 2 to 3 biological replicates. (E) IFN-α2–mediated induction of ACE2 is fully prevented by baricitinib. N = 3 biological replicates. All cytokine concentrations were 10 ng/ml unless stated otherwise. (F) ACE2 in lung organoids is not induced even by very high concentrations of IFN-α2 (50 ng/ml). N = 3 biological replicates. (G) By contrast, IFN-α2 slightly reduces viral load in lung organoids. N = 3 biological replicates. Error bars indicate SEM. A.U., arbitrary units; DMSO, dimethyl sulfoxide.

  • Fig. 4 Baricitinib reverses IFN-mediated gene expression signature alterations.

    (A) Venn diagram depicting the overlap of differentially expressed genes upon IFN-α2 (10 ng/ml) in SARS-CoV-2–infected and uninfected liver spheroids. (B) Circle plots illustrating significantly deregulated genes falling into specific Reactome terminologies in infected and noninfected samples (FDR < 0.05). Circle diameter is indicative for the number of genes per category. (C) Heatmap representation of IFN-responsive genes (n = 832). z scores of normalized TPMs (transcripts per million mapped reads) are plotted (purple, high; white, low). (D) Volcano plot showing the differentially expressed genes in all infected samples upon treatment with baricitinib. Blue and red dots indicate genes that are significantly up- and down-regulated upon IFN treatment. Note that with the exception of SAA1/2, baricitinib results in inverse changes to gene expression compared to IFN, thus ameliorating IFN-induced gene expression alterations. (E) Heatmap visualization of genes for which significant effects on gene expression were detected for baricitinib and IFN.

  • Fig. 5 Baricitinib blocks viral entry of SARS-CoV-2.

    Superresolution dSTORM microscopy of short-term (4 hours) infected liver spheroids stained for nucleocapsid treated with vehicle control (A) or baricitinib (100 nM) (B). (C) Relative mean fluorescence intensities (MFIs) for regions with dimensions of 20 μm by 20 μm of infected and treated organoids and secondary antibody–only controls; five regions per 3D tissue culture. Bars are means ± SD; ***P < 0.001 two-tailed Student’s t test. Ab, antibody; ns, not significant. (D) qPCR analysis of viral load in organotypic primary human liver culture following short-term (4 hours) infections corroborates inhibition of viral entry. (E) Suggested mechanism of dual baricitinib antiviral action on viral entry and inflammatory signaling. Baricitinib inhibits on viral entry by inhibition of the NAKs AAK1 and GAK. In addition, baricitinib blocks inflammatory JAK/STAT signaling, resulting in reduced expression of the IFN target gene and SARS-CoV-2 receptor ACE2. A plasmacytoid dendritic cell is shown on the left, and a hepatocyte is shown on the right.

  • Table 1 Characteristics of patients receiving or not receiving baricitinib in the unmatched and matched study population from the University of Pisa (Italy).

    All data are medians with the interquartile range or number of participants (%). COPD, chronic obstructive pulmonary disease; PaO2/FiO2, ratio of arterial oxygen partial pressure to fractional inspired oxygen; ALT, alanine aminotransferase; ARB, angiotensin-receptor blocker; AST, aspartate aminotransferase; SOFA, sequential organ failure assessment; ULN, upper limit of normal.

    Baricitinib group (n = 37)Control group (n = 142)PS matched control group (n = 37)
    Age66.0 (48.0–84.0)**76.5 (62.5–83)**65 (40–90)
    Male sex27 (73)95 (66.9)26 (70.3)
    Interval between symptom onset and
    admission
    6 (3.5–9)7 (3–8)7 (4–7.5)
    Coexisting conditions
      Hypertension16 (43.2)79 (55.9)18 (48.6)
      Cardiovascular disease9 (24.3)56 (39.4)6 (16.2)
      Solid cancer6 (16.2)22 (15.5)9 (24.3)
      Diabetes7 (18.9)32 (22.5)8 (21.6)
      COPD1 (2.7)*27 (19.0)*0 (0.0)
      Chronic kidney failure2 (5.4)16 (11.3)1 (2.7)
    Charlson comorbidity index2 (0–4)2 (1–5)1 (0–6)
    Medications at baseline
      ACE inhibitor or ARB9 (24.3)43 (30.4)9 (24.3)
      Direct oral anticoagulant or warfarin5 (13.5)24 (16.9)1 (2.7)
    SOFA score3 (1–5)3 (2–4)3 (2–4)
    Baseline PaO2/FiO2242 (143–341)254 (200–298)252 (169–335)
    Noninvasive mechanical ventilation17 (45.9)***19 (13.4)***13 (35.1)
    Baseline laboratory tests
      C-reactive protein (mg/dl)5.7 (0.0–18.0)8.3 (3.7–16.1)11.2 (0.0–25.4)
      Lymphocyte count1010 (400–1620)830 (580–1160)740 (145–1335)
      ALT (U/liter)39 (13–65)25 (16–45)28 (0–58)
      AST (U/liter)43 (12–74)33 (24–50)32 (10–54)
      ALT > 3× ULN1 (2.7%)8 (5.6%)1 (2.7%)
      AST > 3× ULN1 (2.7%)11 (7.7%)2 (5.4%)
      Total bilirubin (mg/dl)0.51 (0.31–0.71)0.49 (0.35–0.77)0.48 (0.08–0.88)
    Concomitant treatment
      Hydroxychloroquine34 (91.9)*102 (71.8)*34 (91.9)
      Other antibiotics33 (89.2)109 (76.8)34 (91.9)
      Proteases inhibitors30 (81.1)*89 (62.7)*29 (78.4)
      LMWH (enoxaparin)36 (97.3)***98 (69)***36 (97.3)
      Steroids27 (73.0)**65 (45.8)**28 (75.7)
    Primary outcome5 (13.5)***66 (46.5)***13 (35.1)*
      Invasive mechanical ventilation4 (10.8)19 (13.4)9 (24.3)
      Died without intubation1 (2.7)47 (33.1)4 (5.4)

    *P < 0.05

    **P < 0.01

    ***P < 0.001

    • Table 2 Characteristics of patients receiving or not receiving baricitinib in the unmatched and matched study population from the Albacete Hospital (Spain).

      IMV, invasive mechanical ventilation. All data are means (SD) or number of participants (%).

      Baricitinib group (n = 46)Control group (n = 376)PS matched control group (n = 46)
      Age80.9 (5.8)82.7 (6.3)80.6 (6.3)
      Male sex30 (65.2)201 (53.5)30 (65.2)
      Interval between symptom onset and
      admission
      7.4 (5.2)7.3 (4.9)7.3 (5.1)
      Coexisting conditions
        Hypertension34 (73.9)296 (78.7)35 (76.1)
        Cardiovascular disease18 (39.1)167 (44.4)15 (32.6)
        Solid cancer2 (4.3)20 (5.3)1 (2.2)
        Diabetes21 (45.7)139 (37.0)14 (30.4)
        COPD11 (23.9)84 (22.3)12 (26.1)
        Chronic kidney failure5 (10.9)64 (17.0)6 (13.0)
      Charlson comorbidity index2.9 (2.3)2.0 (1.9)3.2 (2.8)
      Medications at baseline
        ACE inhibitor or ARB24 (52.2)196 (52.3)26 (56.5)
        Direct oral anticoagulant or warfarin8 (17.4)65 (17.3)4 (8.7)
        Antiaggregants14 (30.4)121 (32.2)15 (32.6)
        Statins23 (50.0)158 (42.0)21 (45.7)
        Insulin9 (19.6)42 (11.2)4 (4.3)
        Oral hypoglycemic agents15 (32.6)109 (29.0)13 (28.3)
        Antidepressants10 (21.7)123 (32.7)11 (23.9)
        Inhaled therapy for COPD12 (26.1)95 (25.3)15 (32.6)
      Baseline PaO2/FiO2284 (109)280 (107)282 (96)
      Baseline laboratory tests
        D-dimer (μg/liter)6944 (18,052)6182 (26,894)5443 (16,872)
        Lactate dehydrogenase (U/liter)387 (136)372 (288)370 (166)
        C-reactive protein (mg/liter)147.2 (98.6)137.6 (118.0)141.8 (145.8)
        Ferritin (ng/ml)1357 (1094)**878 (975)**1039 (927)
        Leucocyte count (per μl)9414 (4790)8986 (4711)7690 (3675)
        Lymphocyte count (per μl)987 (905)967 (777)934 (517)
        Hemoglobin (g/dl)13.7 (2.1)13.2 (2.1)13.7 (3.2)
        Fibrinogen (mg/dl)395 (78)378 (175)375 (70)
        Creatinine (mg/dl)1.2 (0.5)1.3 (0.91)1.1 (0.5)
        AST (U/liter)35.5 (23.4)41.4 (40.3)40 (46)
        Gamma-glutamyltransferase (U/liter)63.3 (49.5)54.2 (74.3)65.5 (119.2)
        ALT (U/liter)33.8 (25.3)30.8 (57.3)31.0 (25.5)
      ALT (U/liter) after treatment, at discharge47.5 (45.8)
      ALT > 2× ULN after treatment, at discharge5 (9.1)
      ALT > 3× ULN after treatment, at discharge3 (5.5)
      Chest x-ray
        Interstitial pattern46 (100)345 (93.0)44 (95.7)
        Opacities38 (82.6)*233 (63.7)*32 (69.6)
        Severity score3.4 (2.1)**2.2 (2.2)**2.4 (2.1)
      Concomitant treatment
        Hydroxychloroquine45 (97.8)*321 (85.4)*46 (100)
        Antibiotics46 (100)365 (97.1)45 (97.8)
        Lopinavir/ritonavir39 (84.8)288 (76.8)42 (91.3)
        LMWH (enoxaparin)46 (100)**322 (85.6)**46 (100)
        Glucocorticoids44 (95.7)***266 (70.7)***42 (91.3)
        Anakinra18 (39.1)***29 (7.7)***10 (21.7)
      Primary outcome (mortality or IMV)9 (19.6)**157 (41.8)**16 (34.8)

      *P < 0.05

      **P < 0.01

      ***P < 0.001

      • Table 3 Common characteristics of patients receiving or not receiving baricitinib in the propensity score–matched populations from the University of Pisa and the Albacete Hospital.

        PS, propensity score matching. All data are means (SD) or number of participants (%).

        Baricitinib group
        (n = 83)
        PS control
        group (n = 83)
        Age74.0 (12.5)74.1 (13.6)
        Male sex43 (51.8)42 (50.6)
        Coexisting conditions
          Hypertension50 (60.2)53 (63.9)
          Cardiovascular disease27 (32.5)21 (25.3)
          Solid cancer8 (9.6)10 (12.0)
          Diabetes28 (33.7)22 (26.5)
          COPD12 (14.5)12 (14.5)
          Chronic kidney failure7 (8.4)7 (8.4)
        Charlson comorbidity index2.7 (2.3)2.8 (2.7)
        Medications at baseline
          ACE inhibitor or ARB33 (39.8)35 (42.2)
        Baseline PaO2/FiO2268 (101)266 (86)
        Baseline laboratory tests
          C-reactive protein (mg/liter)86.0 (100.6)82.2 (123.9)
          Lymphocyte count (per μl)1052 (831)40 (46)
          ALT (U/liter)38.7 (26.5)34.6(29.9)
        Concomitant treatment
          Hydroxychloroquine79 (95.2)80 (96.4)
          Antibiotics79 (95.2)79 (95.2)
          Lopinavir/ritonavir69 (83.1)71 (85.5)
          LMWH82 (98.8)82 (98.8)
          Glucocorticoids71(85.5)70 (84.3)
        Primary outcome14 (16.9)*29 (34.9)*
        Time to outcome19.9 (9.1)**13.1 (9.7)**

        *P < 0.01

        **P < 0.001

        • Table 4 Multivariate Cox regression analyses for the primary outcome in the propensity score–matched populations from the University of Pisa and the Albacete Hospital.

          Selection bias was addressed by propensity score analysis. Briefly, this is a two-phase technique used to estimate a treatment effect in comparative groups selected by nonrandom means. In the first phase of a propensity score analysis, variables that influence selection to group assignment are used to model the probability of receiving treatment (or of being in the reference group, in this case, the baricitinib group). The resulting probability is the propensity score. In the second phase, the propensity score is used to adjust for preexisting group differences in the analysis of the relevant outcomes. There are several ways to use propensity scores such as stratification variables, matching patients on the basis of their propensity score, or their use as a weighting or adjustment variable during multivariate analysis. In the current study, each baricitinib patient was matched to a control patient on the basis of comparable propensity scores. Assuming that all relevant covariates are included in the propensity score model, the group effect observed in a propensity score analysis represents an unbiased estimate of the true treatment effect.

          HR (95% CI)P
          Baricitinib0.29 (0.15–0.58)0.0001
          Age1.01 (0.98–1.04)0.470
          Male sex1.13 (0.54–2.34)0.750
          Hypertension1.31 (0.52–3.32)0.572
          Diabetes0.51 (0.23–1.17)0.113
          Chronic obstructive
          lung disease
          0.51 (0.17–1.54)0.230
          Cardiovascular disease1.41 (0.68–2.92)0.351
          Chronic kidney disease1.45 (0.51–4.15)0.491
          Solid cancer1.18 (0.49–2.87)0.709
          Charlson comorbidity
          index
          1.03 (0.90–1.17)0.680
          Baseline PaO2/FiO21.00 (1.00–1.00)0.823
          Lymphocyte count
          (per μl)
          1.00 (1.00–1.00)0.657
          ALT1.01 (1.00–1.03)0.026
          Hydroxychloroquine2.77 (0.28–27.41)0.384
          Lopinavir/ritonavir1.18 (0.38–3.61)0.776
          Glucocorticoids1.79 (0.60–5.34)0.299
          LMWH0.10 (0.01–1.33)0.081
          Antibiotics2.34 (0.29–18.90)0.427
        • Table 5 Baseline demographic, clinical, and laboratory characteristics of patients with COVID-19 treated with either baricitinib or with standard COVID-19 therapy and results at 2 weeks from the Hospital of Prato.

          Standard univariate statistical tests were performed to compare baricitinib-treated patients to age- and sex-matched controls. These consisted of the Mann-Whitney U test for pairwise comparisons, the Wilcoxon test for paired data, and Fisher’s exact test for categorical variables. Kaplan-Meier product-limit estimation and the log-rank test were used to perform a survival analysis between groups. A dose of 4 mg daily of baricitinib was given for 14 days. SpO2, peripheral capillary oxygen saturation; SBP, systolic blood pressure; DBP, diastolic blood pressure; WBC, white blood cells; MEWS, modified early warning score; CVD, cardiovascular disease; NA, not applicable; IQR, interquartile range; ICU, intensive care unit.

          Features at baseline (all patients
          received hydroxychloroquine and
          lopinavir/ritonavir)
          Baricitinib groupControl group*P value
          Patient number, N (%)23 (100)18 (100)
          Male/female, N (%)20/3 (87/13)14/4 (78/22)0.679
          Age years, median (IQR)62.5 (57.75–72.25)64.1 (55.7–70.1)0.776
          Days interval from symptoms onset
          and therapy starting
          6 (4–6.25)5.5 (4–5.25)0.924
          Cough, N (%)17 (73.9)15 (83.3)0.709
          Dyspnea, N (%)20 (86.9)14 (77.8)0.679
          Sputum production, N (%)7(30.4)9 (50)0.334
          Headache, N (%)8 (34.8)7 (38.9)0.757
          Diarrhea, N (%)5 (21.7)5 (27.8)0.524
          Ageusia/anosmia, N (%)9 (39.1)8 (44.4)0.860
          Hypertension, N (%)5 (21.7)6 (33.3)0.489
          Diabetes, N (%)6 (26)4 (22.2)1.000
          COPD, N (%)5 (21.7)4 (22.2)1.000
          CVD, N (%)4 (17.4)2 /11.1)0.679
          Malignancy, N (%)1 (4.3)1 (5.5)1.000
          Fever (°C)38 (37.5–38.6)37.9 (37.6–38.9)0.912
          Respiratory rate (N/min)18 (16.5–23.2)21 (18–24)0.524
          SpO2 (%)94 (90–95.5)92 (91–93)0.357
          PaO2/FiO2, median (IQR)293 (199–296)271.4 (264–283)0.356
          Pulse rate, median (IQR)84 (72.3–89.1)88 (86–94.5)0.129
          SBP mm/Hg, median (IQR)110 (100–130)105 (98–115.6)0.789
          DBP mm/Hg, median (IQR)70 (60–84)65.5 (60–68.5)0.589
          WBC (×109/liter), median (IQR)7.6 (5.7–10.4)7.9 (7.1–8.6)0.757
          Neutrophils (×109/liter), median (IQR)6,3 (4.2–7.8)7.1 (6.4–8.1)0.224
          Lymphocytes (×109/liter), median (IQR)0.6 (0.5–1.1)0.72 (0.6–0.8)0.524
          Hemoglobin (g/liter), median (IQR)116 (102–133.2)127 (108–136)0.565
          Platelets (×109/liter), median (IQR)207 (174–232)368 (340–415)0.002
          ALT (IU/liter), median (IQR)†27.6 (22.7–53.1)44 (36–50)0.176
          AST (IU/liter), median (IQR)31 (25.2–47.3)44 (34.7–48)0.235
          ALT (IU/liter) > upper normal limit N (%)8 (34.7)9 (50)0.358
          ALT (IU/liter) > upper normal limit,
          median (IQR)
          50 (45.5–62.7)55 (45–68)0.707
          AST (IU/liter) > upper normal limit N/%10110.350
          AST (IU/liter) > upper normal limit,
          median (IQR)
          51.5 (44.5–76.5)67 (55–80)0.302
          Creatinine (mg/dl), median (IQR)1.0 (0.9–1.3)1.1 (0.9–1.2)0.789
          CRP (mg/dl), median (IQR)9.12 (5.9–16.5)4.3 (1.5–5.2)0.001
          Procalcitonin (ng/ml), median (IQR)0.5 (0.3–1.0)1.1 (0.8–2.2)0.589
          IL-6 (pg/ml)‡, median (IQR)29.2 (7.1–39.4)24.2 (5.2–27.6)0.189
          MEWS, median (IQR)2 (1–3.1)3 (3–4)0.544
          Results at 2 weeks after therapy
          ICU admission N (%)05 (33)0.011
          Discharged, N (%)18 (78.2)1 (5.5)<0.0001
          SpO2, median (IQR)97 (94.8–98.1)92.4 (85.5–93.2)<0.0001
          PaO2/FiO2 value, median (IQR)428.7 (306.1–457)277.8 (144–345)0.002
          Lymphocytes (×109/liter), median (IQR)1.3 (1.2–1.9)0.8 (0.6–0.9)0.019
          CRP (mg/dl), median (IQR)0.87 (0.58–2.9)5.2 (2.1–12.3)<0.0001
          IL-6 (pg/ml)‡, median (IQR)6.1 (3.2–7.4)NANA
          ALT (IU/liter), median (IQR)37 (24.1–57.4NANA
          AST (IU/liter), median (IQR)55.4 (28–64.3)NANA

          *Standard therapy group: Patients with COVID-19 under standard respiratory therapy commenced antiretrovirals (Kaletra) and hydroxychloroquine before starting the therapy with baricitinib.

          †Normal ALT and AST values: 10 to 40 IU/liter.

          ‡IL-6 normal value: <7 pg/ml.

          Supplementary Materials

          • Supplementary Materials

            JAK inhibition reduces SARS-CoV-2 liver infectivity and modulates inflammatory responses to reduce morbidity and mortality

            Justin Stebbing, Ginés Sánchez Nievas, Marco Falcone, Sonia Youhanna, Peter Richardson, Silvia Ottaviani, Joanne X. Shen, Christian Sommerauer, Giusy Tiseo, Lorenzo Ghiadoni, Agostino Virdis, Fabio Monzani, Luis Romero Rizos, Francesco Forfori, Almudena Avendaño-Céspedes, Salvatore De Marco, Laura Carrozzi, Fabio Lena, Pedro Manuel Sánchez-Jurado, Leonardo Gianluca Lacerenza, Nencioni Cesira, David Caldevilla-Bernardo, Antonio Perrella, Laura Niccoli, Lourdes Sáez Méndez, Daniela Matarrese, Delia Goletti, Yee-Joo Tan, Vanessa Monteil, George Dranitsaris, Fabrizio Cantini, Alessio Farcomeni, Shuchismita Dutta, Stephen K. Burley, Haibo Zhang, Mauro Pistello, William Li, Marta Mas Romero, Fernando Andrés Pretel, Rafaela Sánchez Simón-Talero, Rafael García-Molina, Claudia Kutte, James H. Felce, Zehra F. Nizami, Andras G. Miklosi, Josef M. Penninger,Francesco Menichetti, Ali Mirazimi, Pedro Abizanda and Volker M. Lauschke

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