Pregnancy, infection, and epigenetic regulation: A complex scenario.

A unique immunological condition, pregnancy ensures fetus from maternal rejection, allows adequate fetal development, and protects against microorganisms. Infections during pregnancy may lead to devastating consequences for pregnant women and fetuses, resulting in the mother's death, miscarriage, premature childbirth, or neonate with congenital infection and severe diseases and defects. Epigenetic (heritable changes in gene expression) mechanisms like DNA methylation, chromatin modification, and gene expression modulation during gestation are linked with the number of defects in the fetus and adolescents. The feto-maternal crosstalk for fetal survival during the entire gestational stages are tightly regulated by various cellular pathways, including epigenetic mechanisms that respond to both internal as well outer environmental factors, which can influence the fetal development across the gestational stages. Due to the intense physiological, endocrinological, and immunological changes, pregnant women are more susceptible to bacterial, viral, parasitic, and fungal infections than the general population. Microbial infections with viruses (LCMV, SARS-CoV, MERS-CoV, and SARS-CoV-2) and bacteria (Clostridium perfringens, Coxiella burnetii, Listeria monocytogenes, Salmonella enteritidis) further increase the risk to maternal and fetal life and developmental outcome. If the infections remain untreated, the possibility of maternal and fetal death exists. This article focused on the severity and susceptibility to infections caused by Salmonella, Listeria, LCMV, and SARS-CoV-2 during pregnancy and their impact on maternal health and the fetus. How epigenetic regulation during pregnancy plays a vital role in deciding the fetus's developmental outcome under various conditions, including infection and other stress. A better understanding of the host-pathogen interaction, the characterization of the maternal immune system, and the epigenetic regulations during pregnancy may help protect the mother and fetus from infection-mediated outcomes.

Threading the Pieces Together: Integrative Perspective on SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has challenged the research community globally to innovate, interact, and integrate findings across hierarchies. Research on SARS-CoV-2 has produced an abundance of data spanning multiple parallels, including clinical data, SARS-CoV-2 genome architecture, host response captured through transcriptome and genetic variants, microbial co-infections (metagenome), and comorbidities. Disease phenotypes in the case of COVID-19 present an intriguing complexity that includes a broad range of symptomatic to asymptomatic individuals, further compounded by a vast heterogeneity within the spectrum of clinical symptoms displayed by the symptomatic individuals. The clinical outcome is further modulated by the presence of comorbid conditions at the point of infection. The COVID-19 pandemic has produced an expansive wealth of literature touching many aspects of SARS-CoV-2 ranging from causal to outcome, predisposition to protective (possible), co-infection to comorbidity, and differential mortality globally. As challenges provide opportunities, the current pandemic's challenge has underscored the need and opportunity to work for an integrative approach that may be able to thread together the multiple variables. Through this review, we have made an effort towards bringing together information spanning across different domains to facilitate researchers globally in pursuit of their response to SARS-CoV-2.

Increased protease-activated receptor 1 autoantibodies are associated with severe COVID-19.

In patients with severe #COVID19, increased levels of autoantibodies against PAR1 were found. These might serve as allosteric agonists of PAR1 on endothelial cells and platelets, and thus might contribute to the pathogenesis of microthrombosis in COVID-19. https://bit.ly/3pqM9Vv.

Integrative systems immunology uncovers molecular networks of the cell cycle that stratify COVID-19 severity.

Several perturbations in the number of peripheral blood leukocytes, such as neutrophilia and lymphopenia associated with Coronavirus disease 2019 (COVID-19) severity, point to systemic molecular cell cycle alterations during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, the landscape of cell cycle alterations in COVID-19 remains primarily unexplored. Here, we performed an integrative systems immunology analysis of publicly available proteome and transcriptome data to characterize global changes in the cell cycle signature of COVID-19 patients. We found significantly enriched cell cycle-associated gene co-expression modules and an interconnected network of cell cycle-associated differentially expressed proteins (DEPs) and genes (DEGs) by integrating the molecular data of 1469 individuals (981 SARS-CoV-2 infected patients and 488 controls [either healthy controls or individuals with other respiratory illnesses]). Among these DEPs and DEGs are several cyclins, cell division cycles, cyclin-dependent kinases, and mini-chromosome maintenance proteins. COVID-19 patients partially shared the expression pattern of some cell cycle-associated genes with other respiratory illnesses but exhibited some specific differential features. Notably, the cell cycle signature predominated in the patients' blood leukocytes (B, T, and natural killer cells) and was associated with COVID-19 severity and disease trajectories. These results provide a unique global understanding of distinct alterations in cell cycle-associated molecules in COVID-19 patients, suggesting new putative pathways for therapeutic intervention.

Increased protease-activated receptor 1 autoantibodies are associated with severe COVID-19

Immune perturbation is a hallmark of Coronavirus Disease 2019 (COVID-19) with ambiguous roles of various immune cell compartments. Plasma cells, responsible for antibody production, have a two-pronged response while mounting an immune defence with 1) physiological immune response producing neutralizing antibodies against protein structures of SARS-CoV-2 and 2) potentially deleterious autoantibody generation. Growing evidence hints towards broad activation of plasma cells and the presence of pathologic autoantibodies (abs) that mediate immune perturbation in acute COVID-19 [1]. Recently, a systematic screening for abs confirmed induction of diverse functional abs in SARS-CoV-2 infection, targeting several immunomodulatory proteins, including cytokines/chemokines and their respective G-protein coupled receptors (GPCR) [1]. Abs against GPCR act as agonistic and allosteric receptor modulators and are linked to chronic inflammatory diseases [2] and, as we recently demonstrated, disease severity in acute COVID-19 [3].

Management of Gynecologic Cancer During COVID-19 Pandemic: South Asian Perspective.

Management of gynecological cancers has suffered during the pandemic, partly due to lockdown and partly due to directing resources to manage COVID-19 patients. Modification of gynecological cancer management during this pandemic is recommended. Cervical cancer patients who present with stage IA1 disease can have a delay of up to 8 weeks for surgical treatment, considering the slow tumor growth rate. Women with stages IA2, IB1, IB2, IIA1 must undergo radical hysterectomy and lymphadenectomy within 6 to 8 weeks. In areas where surgical treatment is not available, patients should be referred for radiation therapy/areas with adequate surgical expertise. The surgical option is attractive for early cancers during the COVID era, as it involves a single visit compared to the multiple visits required for chemoradiation. The value of lymph node staging needs to be reconsidered. Neoadjuvant chemotherapy should be given preference over primary cytoreductive surgery for advanced ovarian cancers. Surgeries, which demand extended surgical time such as Hyperthermic Intraperitoneal Chemotherapy and pelvic exenterations, should be avoided during this pandemic. For patients scheduled for interval surgery after two or three neoadjuvant cycles, six cycles of chemotherapy should be considered before surgery is performed. For early-stage, low-grade endometrial cancer, consideration should be given to medical management until surgery is possible. The above recommendations have been made keeping in mind the geography, patient load, and availability of resources available to health care providers from southeast Asia. They might not be applicable globally and every practitioner should take call regarding patient's management as per availability of resources and loco-regional circumstances. The implementation of recommended international guidelines for the management of gynecologic cancers should take precedence. Each modification to the standard approach should be approved by a multidisciplinary team depending on the condition of the patients and the locoregional circumstances.

Maternal death due to COVID-19, truth or a myth: A narrative review and experience from a teaching hospital in India.

The course of coronavirus disease-2019 (COVID-19) in pregnancy is unpredictable with outcome trends ranging from milder disease with zero mortality to severe forms and deaths in different parts of the world. We did a comprehensive review of the literature to understand maternal deaths due to COVID-19 in detail. The search was conducted in the PubMed, Embase, and Google Scholar databases, using the keywords "maternal mortality", "maternal death", "COVID-19", "septic shock" and "DIC". The search included original articles, review articles, case reports published till date. We found varying case fatality rates ranging from 0.1% to 12.9%. There are various predictors of maternal death, notably the presence of symptoms, comorbidities, severe disease with cytokine storm and multi-organ dysfunction. We also report higher maternal deaths from low-resource regions owing to gaps in expected and delivered maternal care. While reviewing our institutional data, we found 3 maternal deaths related to COVID-19 in pregnancy. We discussed our experience at our institute of three COVID-19 related maternal mortalities to add evidence to the present data. Most maternal deaths occurred in postpartum period. Late referral, loss to follow-up and inadequate care were important determinants of maternal mortality. We concluded that pregnancy cases with or without complications must be considered high risk and addressed judiciously beginning from infection prevention, early diagnosis, disease categorization, and multidisciplinary approach of management to prevent morbidity and mortality. We strongly suggest strengthening the health care delivery system to save pregnant women from dying, particularly in low-resource countries.

COVID-19 Risk Stratification and Mortality Prediction in Hospitalized Indian Patients: Harnessing clinical data for public health benefits.

The variability of clinical course and prognosis of COVID-19 highlights the necessity of patient sub-group risk stratification based on clinical data. In this study, clinical data from a cohort of Indian COVID-19 hospitalized patients is used to develop risk stratification and mortality prediction models. We analyzed a set of 70 clinical parameters including physiological and hematological for developing machine learning models to identify biomarkers. We also compared the Indian and Wuhan cohort, and analyzed the role of steroids. A bootstrap averaged ensemble of Bayesian networks was also learned to construct an explainable model for discovering actionable influences on mortality and days to outcome. We discovered blood parameters, diabetes, co-morbidity and SpO2 levels as important risk stratification features, whereas mortality prediction is dependent only on blood parameters. XGboost and logistic regression model yielded the best performance on risk stratification and mortality prediction, respectively (AUC score 0.83, AUC score 0.92). Blood coagulation parameters (ferritin, D-Dimer and INR), immune and inflammation parameters IL6, LDH and Neutrophil (%) are common features for both risk and mortality prediction. Compared with Wuhan patients, Indian patients with extreme blood parameters indicated higher survival rate. Analyses of medications suggest that a higher proportion of survivors and mild patients who were administered steroids had extreme neutrophil and lymphocyte percentages. The ensemble averaged Bayesian network structure revealed serum ferritin to be the most important predictor for mortality and Vitamin D to influence severity independent of days to outcome. The findings are important for effective triage during strains on healthcare infrastructure.

Impact of Severity of Maternal COVID-19 Infection on Perinatal Outcome and Vertical Transmission Risk: An Ambispective Study From North India

Background In contrast to the first wave, the second COVID-19 wave has taken a huge toll affecting maternal outcomes adversely. The aim of this study was to investigate the consequences of the severity of maternal disease on perinatal outcomes and the risk of vertical transmission and to find out the factors associated with adverse fetomaternal outcomes. Materials and methods This was an ambispective observational study including COVID-19 infected pregnant patients;20-40 years of age irrespective of gestational age admitted at Government Institute of Medical Sciences, UP, India. The patients were divided into two groups: CW 1 (COVID-19 Wave 1): Patients admitted between April 1, 2020 and December 31, 2020 and CW 2 (COVID-19 Wave 2): Patients admitted between April 1, 2021 to May 31, 2021. Data in two groups were compared and analyzed with respect to the clinical profile, laboratory parameters, fetomaternal outcome and the risk of vertical transmission of COVID-19 infection. Results We included 134 eligible patients in the CW1 group and 58 in the CW2 group. Significantly more patients were symptomatic in CW2 (23.1% versus 60.3%, p= <0.001). In CW2, maternal neutrophil-lymphocyte ratio (NLR), C-reactive protein (CRP) and D-Dimer were significantly raised along with abnormal chest x-rays. There was a significant increase in maternal mortality in CW2 (1.5% vs 13.7%;p≤0.001). A total of 76 patients delivered in CW1 and 26 in CW2 with increased incidence of cesarean section (43.4%;42.3%), preterm deliveries (28.2%;37%) and low birth weight (34.6%;25.9%) in both waves, the difference among two groups being statistically insignificant. Compared to CW1, perinatal mortality was significantly increased in CW2 (2.2% vs 15.5%;p<0.001). Though nasopharyngeal swab tested positive in four neonates in CW1 and two neonates in CW2, no evidence of vertical transmission was observed even with increased severity of maternal illness. On regression analysis, D-Dimer and CRP were found to have a positive association with maternal and perinatal mortality.  Conclusion The severity of maternal illness proportionately affects the neonatal outcome with no impact on the risk of vertical transmission of infection. D-Dimer and CRP have emerged as independent predictors for maternal and perinatal mortality and hence can be utilized in obstetrics decision-making.

Instructions for Flow Cytometric Detection of ASC Specks as a Readout of Inflammasome Activation in Human Blood.

Inflammasome activation is linked to the aggregation of the adaptor protein ASC into a multiprotein complex, known as the ASC speck. Redistribution of cytosolic ASC to this complex has been widely used as a readout for inflammasome activation and precedes the downstream proteolytic release of the proinflammatory cytokines, IL-1ß and IL-18. Although inflammasomes are important for many diseases such as periodic fever syndromes, COVID-19, gout, sepsis, atherosclerosis and Alzheimer's disease, only a little knowledge exists on the precise and cell type specific occurrence of inflammasome activation in patient samples ex vivo. In this report, we provide detailed information about the optimal conditions to reliably identify inflammasome activated monocytes by ASC speck formation using a modified flow cytometric method introduced by Sester et al. in 2015. Since no protocol for optimal sample processing exists, we tested human blood samples for various conditions including anticoagulant, time and temperature, the effect of one freeze-thaw cycle for PBMC storage, and the fast generation of a positive control. We believe that this flow cytometric protocol will help researchers to perform high quality translational research in multicenter studies, and therefore provide a basis for investigating the role of the inflammasome in the pathogenesis of various diseases.

Respiratory Co-Infections: Modulators of SARS-CoV-2 Patients' Clinical Sub-Phenotype.

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

Swarm Learning for decentralized and confidential clinical machine learning.

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.

COVID-19 and Menstrual Status: Is Menopause an Independent Risk Factor for SARS Cov-2?

BACKGROUND: COVID-19 has shown a definite association with gender, a predilection for males in terms of morbidity and mortality. The indirect evidence of the protective effect of estrogen has been shown by Channappanavar, in the animal model and Ding T. in a multihospital study from China, suggesting menopause as independent risk factor and estrogen is negatively correlated with severity. OBJECTIVE: Study the clinical profile and outcomes in premenopausal and menopausal. Covid-19-infected women and analyzed the effect of menstrual status on the outcome. MATERIALS AND METHODS: A retrospective cohort study conducted on 147 mild and moderate category COVID-19 females admitted between May and August 2020 using hospital records and telephonic follow-up. Two groups formed based on menstrual status: group-1 (premenopausal/estrogenic) and Group-2 (menopausal/hypoestrogenic). Hospital stay duration was considered as primary, while the category of disease on admission, clinical course, the requirement of oxygen, and mortality and residual symptoms were taken as a secondary outcome to compare the groups. RESULTS: Overall Group-1 had significantly more of mild disease, while Group-2 had moderate cases (39 [76.5%] vs. 14 [14.6%] P < 0.01). Menopausal group has significantly more requirement of oxygen (32 [62.7%] vs. 20 [20.8%]), ventilation (14 [27.5%] vs. 1 [1%]) progression-to-severe disease (23.5% vs. 7.3%) and prolonged hospital stay ([14.1 ± 8.9 vs. 8.6 ± 3.9 days] P < 0.01). However, multivariate logistic regression failed to show a significant association between hospital stay and progression with menopause. Ferritin and residual symptoms found significantly higher in menopausal. CONCLUSIONS: No definite association was found between menopause and COVID-19 outcome with hospital stay duration or disease progression in our study.

COVID-19 and Obstetrical Care: Coping With New Stress.

Objective Our study aimed to assess the mental health outcomes and coping strategies among healthcare workers (HCWs) in an already over-burdened maternity ward and labour room during the coronavirus disease 2019 (COVID-19) pandemic. Methods This cross-sectional questionnaire survey was conducted using Google Forms (Google LLC, Mountain View, CA), which included demographic characteristics, perceived stressors, and validated scales: the Depression, Anxiety and Stress Scale - 21 Items (DASS-21), Insomnia Severity Index, and the Brief Coping Orientation to Problems Experienced (Brief COPE) scale. The results were evaluated and compared among COVID-19 caregivers and other HCWs. Results A total of 184 participants were included in the study, out of which 112 (60.9%) were COVID-19 caregivers. Overall, HCWs managing COVID-19 patients experienced significantly higher levels of depression, anxiety, and stress. They often adopted an avoidant coping style (p-value: 0.006). The results of binary logistic regression analysis revealed that living with family and perceiving multiple stressors appeared to be associated with increased risk of anxiety while being a COVID-19 caregiver and appeared to be a risk factor for stress. Avoidant coping was found to be associated with insomnia while approach coping was less associated with anxiety. The most prevalent stressor among HCWs at our institute was distancing from family and friends (62%) followed by fear of getting infected (51.1%). Compared to other HCWs, the stressors perceived in significantly higher proportion by COVID-19 caregivers included distancing from family and friends (p-value: 0.003), scarcity of workforce (p-value: 0.005), and dealing with non-cooperative patients (p-value: <0.001). Conclusion We would request the immediate attention of the concerned authorities to implement interventions to buffer the impact of COVID-19 in the already stressed-out maternity wards and labour rooms.

Longitudinal Multi-omics Analyses Identify Responses of Megakaryocytes, Erythroid Cells, and Plasmablasts as Hallmarks of Severe COVID-19.

Temporal resolution of cellular features associated with a severe COVID-19 disease trajectory is needed for understanding skewed immune responses and defining predictors of outcome. Here, we performed a longitudinal multi-omics study using a two-center cohort of 14 patients. We analyzed the bulk transcriptome, bulk DNA methylome, and single-cell transcriptome (>358,000 cells, including BCR profiles) of peripheral blood samples harvested from up to 5 time points. Validation was performed in two independent cohorts of COVID-19 patients. Severe COVID-19 was characterized by an increase of proliferating, metabolically hyperactive plasmablasts. Coinciding with critical illness, we also identified an expansion of interferon-activated circulating megakaryocytes and increased erythropoiesis with features of hypoxic signaling. Megakaryocyte- and erythroid-cell-derived co-expression modules were predictive of fatal disease outcome. The study demonstrates broad cellular effects of SARS-CoV-2 infection beyond adaptive immune cells and provides an entry point toward developing biomarkers and targeted treatments of patients with COVID-19.