An Inherently Bifunctional Subset of Foxp3+ T Helper Cells Is Controlled by the Transcription Factor Eos

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In silico dynamics of COVID-19 phenotypes for optimizing clinical management

Understanding the underlying mechanisms of COVID-19 progression and the impact of various pharmaceutical interventions is crucial for the clinical management of the disease. We developed a comprehensive mathematical framework based on the known mechanisms of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, incorporating the renin−angiotensin system and ACE2, which the virus exploits for cellular entry, key elements of the innate and adaptive immune responses, the role of inflammatory cytokines, and the coagulation cascade for thrombus formation. The model predicts the evolution of viral load, immune cells, cytokines, thrombosis, and oxygen saturation based on patient baseline condition and the presence of comorbidities. Model predictions were validated with clinical data from healthy people and COVID-19 patients, and the results were used to gain insight into identified risk factors of disease progression including older age; comorbidities such as obesity, diabetes, and hypertension; and dysregulated immune response. We then simulated treatment with various drug classes to identify optimal therapeutic protocols. We found that the outcome of any treatment depends on the sustained response rate of activated CD8⁺ T cells and sufficient control of the innate immune response. Furthermore, the best treatment—or combination of treatments—depends on the preinfection health status of the patient. Our mathematical framework provides important insight into SARS-CoV-2 pathogenesis and could be used as the basis for personalized, optimal management of COVID-19.

COVID-19 has created unprecedented challenges for the health care system, and, until an effective vaccine is developed and made widely available, treatment options are limited. A challenge to the development of optimal treatment strategies is the extreme heterogeneity of presentation. Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in a syndrome that ranges in severity from asymptomatic to multiorgan failure and death. In addition to local complications in the lung, the virus can cause systemic inflammation and disseminated microthrombosis, which can cause stroke, myocardial infarction, or pulmonary emboli (1–4). Risk factors for poor COVID-19 outcome include advanced age, obesity, diabetes, and hypertension (5–13).Computational analyses can provide insights into the transmission, control, progression, and underlying mechanisms of infectious diseases. Indeed, epidemiological and statistical modeling has been used for COVID-19, providing powerful insights into comorbidities, transmission dynamics, and control of the disease (14–17). However, to date, these analyses have been population dynamics models of SARS-CoV-2 infection and transmission or correlative analyses of COVID-19 comorbidities and treatment response. Simple viral dynamics models have been also developed and used to predict the SARS-CoV-2 response to antiviral drugs (18, 19). These models, however, do not explicitly consider the biological or physiological mechanisms underlying disease progression or the time course of response to various therapeutic interventions, and only a few more-sophisticated models have been developed toward this direction (20, 21).Several therapies targeting various aspects of COVID-19 pathogenesis have been proposed and have either completed—or are currently being tested in—clinical trials (22). Despite strong biologic rationale, these treatments have generally produced conflicting results in the clinic. For example, trials of antiviral therapies (e.g., remdesivir) have been mixed: The original trial from China failed (23), a subsequent trial in the United States led to approval of remdesivir in the United States and other countries (24), and the recent results of the World Health Organization Solidarity trial again show no benefit (25). Other antiviral drugs alone or in combination are also showing promise (26).Other potential treatments include antiinflammatory drugs and antithrombotic agents. Because of the systemic inflammation seen in many patients, antiinflammatory drugs have been tested, including anti-IL6/IL6R therapy (e.g., tocilizumab, siltuximab) and anti-JAK1/2 drugs (e.g., barcitinib). It is not clear whether these drugs will be effective as stand-alone treatments, particularly after the recent failure of tocilizumab in a phase III trial (1, 27–29). In addition, given that a common complication of COVID-19 is the development of coagulopathies with microvascular thrombi potentially leading to the dysfunction of multiple organ systems (2, 3), antithrombotic drugs (e.g., low molecular weight heparin) are being tested. Recognizing the interactions of COVID-19 with the immune system (30), the corticosteroid dexamethasone has been tested, showing some promising results. Given the large range of patient comorbidities, disease severities, and variety of complications such as thrombosis, it is likely that patients will have heterogeneous responses to any given therapy, and such heterogeneity will continue to be a challenge for clinical trials of unselected COVID-19 patients (31).Here, we developed a systems biology-based mathematical model to address this urgent need. Our model incorporates the known mechanisms of SARS-CoV-2 pathogenesis and the potential mechanisms of action of various therapeutic interventions that have been tested in COVID-19 patients. In previous work, we have exploited angiotensin receptor blockers (ARBs) and angiotensin converting enzyme inhibitors (ACEis) for the improvement of cancer therapies and developed mathematical models of the renin−angiotensin system in the context of cancer desmoplasia (32–35). Using a similar approach, we developed a detailed model that includes lung infection by the SARS-CoV-2 virus and a pharmacokinetic/pharmacodynamic (PK/PD) model of infection and thrombosis to simulate events that take place throughout the body during COVID-19 progression (Fig. 1 and SI Appendix, Fig. S1). The model is first validated against clinical data of healthy people and COVID-19 patients and then used to simulate disease progression in patients with specific comorbidities. Subsequently, we present model predictions for various therapies currently employed for treatment of COVID-19 alone or in combination, and we identify protocols for optimal clinical management for each of the clinically observed COVID-19 phenotypes.Open in a separate windowFig. 1.Schematic of the detailed lung model. The model incorporates the virus infection of epithelial and endothelial cells, the RAS, T cells activation and immune checkpoints, the known IL6 pathways, neutrophils, and macrophages, as well as the formation of NETs, and the coagulation cascade. The lung model is coupled with a PK/PD model for the virus and thrombi dissemination through the body.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Causes, consequences, and remedies for growth-induced solid stress in murine and human tumors

The presence of growth-induced solid stresses in tumors has been suspected for some time, but these stresses were largely estimated using mathematical models. Solid stresses can deform the surrounding tissues and compress intratumoral lymphatic and blood vessels. Compression of lymphatic vessels elevates interstitial fluid pressure, whereas compression of blood vessels reduces blood flow. Reduced blood flow, in turn, leads to hypoxia, which promotes tumor progression, immunosuppression, inflammation, invasion, and metastasis and lowers the efficacy of chemo-, radio-, and immunotherapies. Thus, strategies designed to alleviate solid stress have the potential to improve cancer treatment. However, a lack of methods for measuring solid stress has hindered the development of solid stress-alleviating drugs. Here, we present a simple technique to estimate the growth-induced solid stress accumulated within animal and human tumors, and we show that this stress can be reduced by depleting cancer cells, fibroblasts, collagen, and/or hyaluronan, resulting in improved tumor perfusion. Furthermore, we show that therapeutic depletion of carcinoma-associated fibroblasts with an inhibitor of the sonic hedgehog pathway reduces solid stress, decompresses blood and lymphatic vessels, and increases perfusion. In addition to providing insights into the mechanopathology of tumors, our approach can serve as a rapid screen for stress-reducing and perfusion-enhancing drugs.     

Tolerance to apoptotic cells is regulated by indoleamine 2,3-dioxygenase

Tolerance to self-antigens present in apoptotic cells is critical to maintain immune-homeostasis and prevent systemic autoimmunity. However, mechanisms that sustain self-tolerance are poorly understood. Here we show that systemic administration of apoptotic cells to mice induced splenic expression of the tryptophan catabolizing enzyme indoleamine 2,3-dioxygenase (IDO). IDO expression was confined to the splenic marginal zone and was abrogated by depletion of CD169(+) cells. Pharmacologic inhibition of IDO skewed the immune response to apoptotic cells, resulting in increased proinflammatory cytokine production and increased effector T-cell responses toward apoptotic cell-associated antigens. Presymptomatic lupus-prone MRL(lpr/lpr) mice exhibited abnormal elevated IDO expression in the marginal zone and red pulp and inhibition of IDO markedly accelerated disease progression. Moreover, chronic exposure of IDO-deficient mice to apoptotic cells induced a lupus-like disease with serum autoreactivity to double-stranded DNA associated with renal pathology and increased mortality. Thus, IDO limits innate and adaptive immunity to apoptotic self-antigens and IDO-mediated regulation inhibits inflammatory pathology caused by systemic autoimmune disease.     

Cell-autonomous control of interferon type I expression by indoleamine 2,3-dioxygenase in regulatory CD19+ dendritic cells

Following CD80/86 (B7) and TLR9 ligation, small subsets of splenic dendritic cells expressing CD19 (CD19(+) DC) acquire potent T cell regulatory functions due to induced expression of the intracellular enzyme indoleamine 2,3-dioxygenase (IDO), which catabolizes tryptophan. In CD19(+) DC, IFN type I (IFN-alpha) is the obligate inducer of IDO. We now report that IFN-alpha production needed to stimulate high-level expression of IDO following B7 ligation is itself dependent on basal levels of IDO activity. Genetic and pharmacologic ablation of IDO completely abrogated IFN-alpha production by CD19(+) DC after B7 ligation. In contrast, IDO ablation did not block IFN-alpha production by CD19(+) DC after TLR9 ligation. IDO-mediated control of IFN-alpha production depended on tryptophan depletion as adding excess tryptophan also blocked IFN-alpha expression after B7 ligation. Consistent with this, DC from mice deficient in general control of non-derepressible-2 (GCN2)-kinase, a component of the cellular stress response to amino acid withdrawal, did not produce IFN-alpha following B7 ligation, but produced IFN-alpha after TLR9 ligation. Thus, B7 and TLR9 ligands stimulate IFN-alpha expression in CD19(+) DC via distinct signaling pathways. In the case of B7 ligation, IDO activates cell-autonomous signals essential for IFN-alpha production, most likely by activating the GCN2-kinase-dependent stress response.     

Organic cation transporter 3: Keeping the brake on extracellular serotonin in serotonin-transporter-deficient mice

Mood disorders cause much suffering and are the single greatest cause of lost productivity worldwide. Although multiple medications, along with behavioral therapies, have proven effective for some individuals, millions of people lack an effective therapeutic option. A common serotonin (5-HT) transporter (5-HTT/SERT, SLC6A4) polymorphism is believed to confer lower 5-HTT expression in vivo and elevates risk for multiple mood disorders including anxiety, alcoholism, and major depression. Importantly, this variant is also associated with reduced responsiveness to selective 5-HT reuptake inhibitor antidepressants. We hypothesized that a reduced antidepressant response in individuals with a constitutive reduction in 5-HTT expression could arise because of the compensatory expression of other genes that inactivate 5-HT in the brain. A functionally upregulated alternate transporter for 5-HT may prevent extracellular 5-HT from rising to levels sufficiently high enough to trigger the adaptive neurochemical events necessary for therapeutic benefit. Here we demonstrate that expression of the organic cation transporter type 3 (OCT3, SLC22A3), which also transports 5-HT, is upregulated in the brains of mice with constitutively reduced 5-HTT expression. Moreover, the OCT blocker decynium-22 diminishes 5-HT clearance and exerts antidepressant-like effects in these mice but not in WT animals. OCT3 may be an important transporter mediating serotonergic signaling when 5-HTT expression or function is compromised.     

Experimental vaccine protection against feline immunodeficiency virus.

Infection of domestic cats with the feline immunodeficiency virus (FIV) represents an important veterinary health problem and a useful animal model for the development of vaccines against acquired immunodeficiency syndrome (AIDS). Two experimental FIV vaccines have been developed; one consisting of fixed infected cells (Vaccine 1), the other of inactivated whole virus (Vaccine 2). After 4-6 immunizations over 2-5 months, both vaccines induced a strong FIV-specific immune response including neutralizing antibody and T-cell proliferation. Vaccine 1 protected 6 of 9 and Vaccine 2 protected 5 of 6 recipient cats against any detectable infection with a low dose (10 animal ID50) of FIV given intraperitoneally 2 weeks after the final boost. One additional cat in each vaccine group had a transient infection at 5-7 weeks postchallenge following which virus could no longer be detected. Thus, a total of 13 of 15 vaccinated cats were protected against persistent infection. By contrast, 13 of 13 controls were persistently infected by this challenge. The infected cell vaccine failed to protect against a higher dose (5 x 10(4) ID50) of FIV. These results indicate that vaccine prophylaxis against natural FIV infection should be achievable and enhance optimism of the prospect of developing an effective AIDS vaccine for humans.     

Inhibition of indoleamine 2,3-dioxygenase (IDO) enhances elimination of virus-infected macrophages in an animal model of HIV-1 encephalitis

Indoleamine 2,3-dioxygenase (IDO) is the rate-limiting enzyme in the kynurenine pathway of tryptophan metabolism. IDO activity is linked with immunosuppression by its ability to inhibit lymphocyte proliferation, and with neurotoxicity through the generation of quinolinic acid and other toxins. IDO is induced in macrophages by HIV-1 infection, and it is up regulated in macrophages in human brain tissue with HIV-1 encephalitis (HIVE). Using a model of HIVE, we investigated whether IDO inhibitor 1-methyl-d-tryptophan (1-MT) could affect the generation of cytotoxic T lymphocytes (CTLs) and clearance of virus-infected macrophages from the brain. Severe combined immunodeficient mice were reconstituted with human peripheral blood lymphocytes, and encephalitis was induced by intracranial injection of autologous HIV-1-infected monocyte-derived macrophages (MDMs). Animals treated with 1-MT demonstrated increased numbers of human CD3+, CD8+, CD8+/interferon-gamma+ T cells, and HIV-1(gag/pol)-specific CTLs in peripheral blood compared with controls. At week 2 after MDM injection in the basal ganglia, mice treated with 1-MT showed a 2-fold increase in CD8+ T lymphocytes in the areas of the brain containing HIV-1-infected MDMs compared with untreated controls. By week 3, 1-MT-treated mice showed 89% reduction in HIV-infected MDMs in brain as compared with controls. Thus, manipulation of immunosuppressive IDO activity in HIVE may enhance the generation of HIV-1-specific CTLs, leading to elimination of HIV-1-infected macrophages in brain.     

Socioeconomic Disparities in Telephone-Based Treatment of Tobacco Dependence

Objectives. We examined socioeconomic disparities in tobacco dependence treatment outcomes from a free, proactive telephone counseling quitline.Methods. We delivered cognitive–behavioral treatment and nicotine patches to 6626 smokers and examined socioeconomic differences in demographic, clinical, environmental, and treatment use factors. We used logistic regressions and generalized estimating equations (GEE) to model abstinence and account for socioeconomic differences in the models.Results. The odds of achieving long-term abstinence differed by socioeconomic status (SES). In the GEE model, the odds of abstinence for the highest SES participants were 1.75 times those of the lowest SES participants. Logistic regression models revealed no treatment outcome disparity at the end of treatment, but significant disparities 3 and 6 months after treatment.Conclusions. Although quitlines often increase access to treatment for some lower SES smokers, significant socioeconomic disparities in treatment outcomes raise questions about whether current approaches are contributing to tobacco-related socioeconomic health disparities. Strategies to improve treatment outcomes for lower SES smokers might include novel methods to address multiple factors associated with socioeconomic disparities.In the United States, the prevalence of daily smoking among lower socioeconomic status (SES) groups is 3 to 4 times higher than that of higher SES groups and a leading contributor to socioeconomic health disparities.1–5 Comprehensive tobacco control programs can reduce these disparities by providing all smokers with effective treatment for tobacco dependence; however, significant socioeconomic disparities in treatment outcomes are observed in many treatment settings, raising concerns about contributing to or at least maintaining existing disparities with these approaches.6–14 Treatment delivered through telephone quitlines has become widely available in the United States and the United Kingdom.15 Proactive quitlines attract a large proportion of lower SES smokers16–18 and smokers with different demographic and clinical characteristics than in-person, community-based treatments.16,19,20 Because of their ubiquitous nature and because they appear to be especially accessible and attractive to lower SES smokers,16,17,18 quitlines have the potential to attenuate tobacco-related disparities; however, if quitlines also demonstrate socioeconomic disparities in treatment outcomes, then this would strengthen concerns about current approaches contributing to or maintaining these disparities.SES ideally incorporates the social and economic factors that influence what position individuals or groups hold in a societal structure.21,22 In health research, SES is a broad construct describing relative access to basic resources required to achieve or maintain good health.23,24 Consistent with leading conceptual models of health disparities,23–26 SES is empirically related to smoking cessation through complex reciprocal relations among clinical, environmental, and treatment utilization factors including stress, coping resources, psychological factors, exposure to other smokers, and use of treatment resources.6,27–32Cognitive–behavioral treatment (CBT) provided through proactive quitlines is a practical innovation that attracts a promising number of lower SES smokers.15–17,33 Although not targeted to or tailored for lower SES groups, CBT, when delivered appropriately, addresses individuals’ treatment-related clinical characteristics (e.g., stress, coping, dependence level, motivation, self-efficacy, environmental challenges). Nonetheless, significant disparities have been found in CBT treatment outcomes in many tobacco treatment settings.6–14 Quitlines treat smokers with different characteristics than in-person treatment,16,19,20 however, and thus might not demonstrate the same disparities as in-person CBT treatment.6–13We investigated socioeconomic disparities in tobacco dependence treatment outcomes using data from a proactive quitline in Arkansas in operation from 2005 to 2008. We used statistical modeling of abstinence at the end of treatment (EOT) and 3 and 6 months after treatment to examine the independent contribution of SES to treatment outcomes controlling for other factors. Consistent with findings from community-based treatment, we hypothesized that after accounting for demographic, clinical, environmental, and treatment utilization factors, the lowest SES participants would be least likely to achieve long-term abstinence.