Cardiovascular complications of diabetes: role of non-coding RNAs in the crosstalk between immune and cardiovascular systems.

Diabetes mellitus, a group of metabolic disorders characterized by high levels of blood glucose caused by insulin defect or impairment, is a major risk factor for cardiovascular diseases and related mortality. Patients with diabetes experience a state of chronic or intermittent hyperglycemia resulting in damage to the vasculature, leading to micro- and macro-vascular diseases. These conditions are associated with low-grade chronic inflammation and accelerated atherosclerosis. Several classes of leukocytes have been implicated in diabetic cardiovascular impairment. Although the molecular pathways through which diabetes elicits an inflammatory response have attracted significant attention, how they contribute to altering cardiovascular homeostasis is still incompletely understood. In this respect, non-coding RNAs (ncRNAs) are a still largely under-investigated class of transcripts that may play a fundamental role. This review article gathers the current knowledge on the function of ncRNAs in the crosstalk between immune and cardiovascular cells in the context of diabetic complications, highlighting the influence of biological sex in such mechanisms and exploring the potential role of ncRNAs as biomarkers and targets for treatments. The discussion closes by offering an overview of the ncRNAs involved in the increased cardiovascular risk suffered by patients with diabetes facing Sars-CoV-2 infection.

The Drosophila melanogaster ACE2 ortholog genes are differently expressed in obesity/diabetes and aging models: Implications for COVID-19 pathology.

The Spike glycoprotein of SARS-CoV-2, the virus responsible for coronavirus disease 2019, binds to its ACE2 receptor for internalization in the host cells. Elderly individuals or those with subjacent disorders, such as obesity and diabetes, are more susceptible to COVID-19 severity. Additionally, several SARS-CoV-2 variants appear to enhance the Spike-ACE2 interaction, which increases transmissibility and death. Considering that the fruit fly is a robust animal model in metabolic research and has two ACE2 orthologs, Ance and Acer, in this work, we studied the effects of two hypercaloric diets (HFD and HSD) and aging on ACE2 orthologs mRNA expression levels in Drosophila melanogaster. To complement our work, we analyzed the predicted binding affinity between the Spike protein with Ance and Acer. We show for the first time that Ance and Acer genes are differentially regulated and dependent on diet and age in adult flies. At the molecular level, Ance and Acer proteins exhibit the potential to bind to the Spike protein in different regions, as shown by a molecular docking approach. Acer, in particular, interacts with the Spike protein in the same region as in humans. Overall, we suggest that the D. melanogaster is a promising animal model for translational studies on COVID-19 associated risk factors and ACE2.

Gene Networks of Hyperglycemia, Diabetic Complications, and Human Proteins Targeted by SARS-CoV-2: What Is the Molecular Basis for Comorbidity?

People with diabetes are more likely to have severe COVID-19 compared to the general population. Moreover, diabetes and COVID-19 demonstrate a certain parallelism in the mechanisms and organ damage. In this work, we applied bioinformatics analysis of associative molecular networks to identify key molecules and pathophysiological processes that determine SARS-CoV-2-induced disorders in patients with diabetes. Using text-mining-based approaches and ANDSystem as a bioinformatics tool, we reconstructed and matched networks related to hyperglycemia, diabetic complications, insulin resistance, and beta cell dysfunction with networks of SARS-CoV-2-targeted proteins. The latter included SARS-CoV-2 entry receptors (ACE2 and DPP4), SARS-CoV-2 entry associated proteases (TMPRSS2, CTSB, and CTSL), and 332 human intracellular proteins interacting with SARS-CoV-2. A number of genes/proteins targeted by SARS-CoV-2 (ACE2, BRD2, COMT, CTSB, CTSL, DNMT1, DPP4, ERP44, F2RL1, GDF15, GPX1, HDAC2, HMOX1, HYOU1, IDE, LOX, NUTF2, PCNT, PLAT, RAB10, RHOA, SCARB1, and SELENOS) were found in the networks of vascular diabetic complications and insulin resistance. According to the Gene Ontology enrichment analysis, the defined molecules are involved in the response to hypoxia, reactive oxygen species metabolism, immune and inflammatory response, regulation of angiogenesis, platelet degranulation, and other processes. The results expand the understanding of the molecular basis of diabetes and COVID-19 comorbidity.

Comparative study of CNR1 and CNR2 cannabinoid receptors expression levels in COVID-19 patients with and without diabetes mellitus: Recommendations for future research targets.

BACKGROUND AND AIMS: The COVID-19 pandemic has prompted researchers to look for effective therapeutic targets. The effect of endocannabinoid system against infectious diseases is investigated for several years. In this study, we evaluated the expression level of CNR1 and CNR2 genes in patients with COVID-19 with and without diabetes to provide new insights regarding these receptors and their potential effect in COVID-19 disease. METHODS: In this study, peripheral blood monocytes cells (PBMCs) were isolated from eight different groups including COVID-19 patients, diabetic patients, and healthy individuals. RNA were extracted to evaluate the expression level of CNR1 and CNR2 genes using real-time PCR. The correlation between the expression levels of these genes in different groups were assessed. RESULTS: A total of 80 samples were divided into 8 groups, with each group consisting of ten samples. When comparing severe and moderate COVID-19 groups to healthy control group, the expression levels of the CNR1 and CNR2 genes were significantly higher in the severe and moderate COVID-19 groups. There were no significant differences between the mild COVID-19 group and the healthy control group. It was found that the expression levels of these genes in patients with diabetes who were infected with SARS-COV-2 did not differ across COVID-19 groups with varying severity, but they were significantly higher when compared to healthy controls. CONCLUSION: Our study suggests the possible role of endocannabinoid system during SARS-COV-2 pathogenicity as the expression of CNR1 and CNR2 were elevated during the disease.

Duodenal Mucosal Expression of COVID-19-Related Genes in Health, Diabetic Gastroenteropathy, and Functional Dyspepsia.

CONTEXT: SARS-CoV-2 infects the gastrointestinal tract and may be associated with symptoms that resemble diabetic gastroparesis. Why patients with diabetes who contract COVID-19 are more likely to have severe disease is unknown. OBJECTIVE: We aimed to compare the duodenal mucosal expression of SARS-CoV-2 and inflammation-related genes in diabetes gastroenteropathy (DGE), functional dyspepsia (FD), and healthy controls. METHODS: Gastrointestinal transit, and duodenal mucosal mRNA expression of selected genes were compared in 21 controls, 39 DGE patients, and 37 FD patients from a tertiary referral center. Pathway analyses were performed. RESULTS: Patients had normal, delayed (5 FD [13%] and 13 DGE patients [33%]; P = 0.03 vs controls), or rapid (5 FD [12%] and 5 DGE [12%]) gastric emptying (GE). Compared with control participants, 100 SARS-CoV-2-related genes were increased in DGE (FDR < 0.05) vs 13 genes in FD; 71 of these 100 genes were differentially expressed in DGE vs FD but only 3 between DGE patients with normal vs delayed GE. Upregulated genes in DGE include the SARS-CoV2 viral entry genes CTSL (|Fold change [FC]|=1.16; FDR < 0.05) and CTSB (|FC|=1.24; FDR < 0.05) and selected genes involved in viral replication (eg, EIF2 pathways) and inflammation (CCR2, CXCL2, and LCN2, but not other inflammation-related pathways eg, IL-2 and IL-6 signaling). CONCLUSION: Several SARS-CoV-2-related genes were differentially expressed between DGE vs healthy controls and vs FD but not between DGE patients with normal vs delayed GE, suggesting that the differential expression is related to diabetes per se. The upregulation of CTSL and CTSB and replication genes may predispose to SARS-CoV2 infection of the gastrointestinal tract in diabetes.

Shared genomic architecture between COVID-19 severity and numerous clinical and physiologic parameters revealed by LD score regression analysis.

The COVID-19 pandemic has produced broad clinical manifestations, from asymptomatic infection to hospitalization and death. Despite progress from genomic and clinical epidemiology research, risk factors for developing severe COVID-19 are incompletely understood and identification of modifiable risk factors is desperately needed. We conducted linkage disequilibrium score regression (LDSR) analysis to estimate cross-trait genetic correlation between COVID-19 severity and various polygenic phenotypes. To attenuate the genetic contribution of smoking and BMI, we further conducted sensitivity analyses by pruning genomic regions associated with smoking/BMI and repeating LDSR analyses. We identified robust positive associations between the genetic architecture of severe COVID-19 and both BMI and smoking. We observed strong positive genetic correlation (rg) with diabetes (rg = 0.25) and shortness of breath walking on level ground (rg = 0.28) and novel protective associations with vitamin E (rg = - 0.53), calcium (rg = - 0.33), retinol (rg = - 0.59), Apolipoprotein A (rg = - 0.13), and HDL (rg = - 0.17), but no association with vitamin D (rg = - 0.02). Removing genomic regions associated with smoking and BMI generally attenuated the associations, but the associations with nutrient biomarkers persisted. This study provides a comprehensive assessment of the shared genetic architecture of COVID-19 severity and numerous clinical/physiologic parameters. Associations with blood and plasma-derived traits identified biomarkers for Mendelian randomization studies to explore causality and nominates therapeutic targets for clinical evaluation.

Deciphering the link between Diabetes mellitus and SARS-CoV-2 infection through differential targeting of microRNAs in the human pancreas.

PURPOSE: Coronavirus Disease 2019 (COVID-19) severity and Diabetes mellitus affect each other bidirectionally. However, the cause of severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection on the incidence of diabetes is unclear. In the SARS-CoV-2-infected cells, host microRNAs (miRNAs) may target the native gene transcripts as well as the viral genomic and subgenomic RNAs. Here, we investigated the role of miRNAs in linking Diabetes to SARS-CoV-2 infection in the human pancreas. METHODS: Differential gene expression and disease enrichment analyses were performed on an RNA-Seq dataset of human embryonic stem cell-derived (hESC) mock-infected and SARS-CoV-2-infected pancreatic organoids to obtain the dysregulated Diabetes-associated genes. The miRNA target prediction for the Diabetes-associated gene transcripts and the SARS-CoV-2 RNAs has been made to determine the common miRNAs targeting them. Minimum Free Energy (MFE) analysis was done to identify the miRNAs, preferably targeting SARS-CoV-2 RNAs over the Diabetes-associated gene transcripts. RESULTS: The gene expression and disease enrichment analyses of the RNA-Seq data have revealed five biomarker genes, i.e., CP, SOCS3, AGT, PSMB8 and CFB that are associated with Diabetes and get significantly upregulated in the pancreas following SARS-CoV-2-infection. Four miRNAs, i.e., hsa-miR-298, hsa-miR-3925-5p, hsa-miR-4691-3p and hsa-miR-5196-5p, showed preferential targeting of the SARS-CoV-2 genome over the cell's Diabetes-associated messenger RNAs (mRNAs) in the human pancreas. CONCLUSION: Our study proposes that the differential targeting of the Diabetes-associated host genes by the miRNAs may lead to diabetic complications or new-onset Diabetes that can worsen the condition of COVID-19 patients.

ACE Gene Variants Rise the Risk of Severe COVID-19 in Patients With Hypertension, Dyslipidemia or Diabetes: A Spanish Pilot Study.

Coronavirus disease 19 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection continues to scale and threaten human health and public safety. It is essential to identify those risk factors that lead to a poor prognosis of the disease. A predisposing host genetic background could be one of these factors that explain the interindividual variability to COVID-19 severity. Thus, we have studied whether the rs4341 and rs4343 polymorphisms of the angiotensin converting enzyme (ACE) gene, key regulator of the renin-aldosterone-angiotensin system (RAAS), could explain the different outcomes of 128 COVID-19 patients with diverse degree of severity (33 asymptomatic or mildly symptomatic, 66 hospitalized in the general ward, and 29 admitted to the ICU). We found that G allele of rs4341 and rs4343 was associated with severe COVID-19 in hypertensive patients, independently of gender (p<0.05). G-carrier genotypes of both polymorphisms were also associated with higher mortality (p< 0.05) and higher severity of COVID-19 in dyslipidemic (p<0.05) and type 2 diabetic patients (p< 0.01). The association of G alleles with disease severity was adjusted for age, sex, BMI and number of comorbidities, suggesting that both the metabolic comorbidities and the G allele act synergistically on COVID-19 outcome. Although we did not find a direct association between serum ACE levels and COVID-19 severity, we found higher levels of ACE in the serum of patients with the GG genotype of rs4341 and rs4343 (p<0.05), what could explain the higher susceptibility to develop severe forms of the disease in patients with the GG genotype, in addition to hypertension and dyslipidemia. In conclusion, our preliminary study suggests that the G-containing genotypes of rs4341 and rs4343 confer an additional risk of adverse COVID-19 prognosis. Thus, rs4341 and rs4343 polymorphisms of ACE could be predictive markers of severity of COVID-19 in those patients with hypertension, dyslipidemia or diabetes. The knowledge of these genetic data could contribute to precision management of SARS-CoV-2 infected patients when admitted to hospital.

Decreased inhibition of exosomal miRNAs on SARS-CoV-2 replication underlies poor outcomes in elderly people and diabetic patients.

Elderly people and patients with comorbidities are at higher risk of COVID-19 infection, resulting in severe complications and high mortality. However, the underlying mechanisms are unclear. In this study, we investigate whether miRNAs in serum exosomes can exert antiviral functions and affect the response to COVID-19 in the elderly and people with diabetes. First, we identified four miRNAs (miR-7-5p, miR-24-3p, miR-145-5p and miR-223-3p) through high-throughput sequencing and quantitative real-time PCR analysis, that are remarkably decreased in the elderly and diabetic groups. We further demonstrated that these miRNAs, either in the exosome or in the free form, can directly inhibit S protein expression and SARS-CoV-2 replication. Serum exosomes from young people can inhibit SARS-CoV-2 replication and S protein expression, while the inhibitory effect is markedly decreased in the elderly and diabetic patients. Moreover, three out of the four circulating miRNAs are significantly increased in the serum of healthy volunteers after 8-weeks' continuous physical exercise. Serum exosomes isolated from these volunteers also showed stronger inhibitory effects on S protein expression and SARS-CoV-2 replication. Our study demonstrates for the first time that circulating exosomal miRNAs can directly inhibit SARS-CoV-2 replication and may provide a possible explanation for the difference in response to COVID-19 between young people and the elderly or people with comorbidities.

SARS-CoV-2 Cell Entry Factors ACE2 and TMPRSS2 Are Expressed in the Microvasculature and Ducts of Human Pancreas but Are Not Enriched in ß Cells.

Isolated reports of new-onset diabetes in individuals with COVID-19 have led to the hypothesis that SARS-CoV-2 is directly cytotoxic to pancreatic islet ß cells. This would require binding and entry of SARS-CoV-2 into ß cells via co-expression of its canonical cell entry factors, angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2); however, their expression in human pancreas has not been clearly defined. We analyzed six transcriptional datasets of primary human islet cells and found that ACE2 and TMPRSS2 were not co-expressed in single ß cells. In pancreatic sections, ACE2 and TMPRSS2 protein was not detected in ß cells from donors with and without diabetes. Instead, ACE2 protein was expressed in islet and exocrine tissue microvasculature and in a subset of pancreatic ducts, whereas TMPRSS2 protein was restricted to ductal cells. These findings reduce the likelihood that SARS-CoV-2 directly infects ß cells in vivo through ACE2 and TMPRSS2.

Discovering common pathogenetic processes between COVID-19 and diabetes mellitus by differential gene expression pattern analysis.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the newly discovered coronavirus, SARS-CoV-2. Increased severity of COVID-19 has been observed in patients with diabetes mellitus (DM). This study aimed to identify common transcriptional signatures, regulators and pathways between COVID-19 and DM. We have integrated human whole-genome transcriptomic datasets from COVID-19 and DM, followed by functional assessment with gene ontology (GO) and pathway analyses. In peripheral blood mononuclear cells (PBMCs), among the upregulated differentially expressed genes (DEGs), 32 were found to be commonly modulated in COVID-19 and type 2 diabetes (T2D), while 10 DEGs were commonly downregulated. As regards type 1 diabetes (T1D), 21 DEGs were commonly upregulated, and 29 DEGs were commonly downregulated in COVID-19 and T1D. Moreover, 35 DEGs were commonly upregulated in SARS-CoV-2 infected pancreas organoids and T2D islets, while 14 were commonly downregulated. Several GO terms were found in common between COVID-19 and DM. Prediction of the putative transcription factors involved in the upregulation of genes in COVID-19 and DM identified RELA to be implicated in both PBMCs and pancreas. Here, for the first time, we have characterized the biological processes and pathways commonly dysregulated in COVID-19 and DM, which could be in the next future used for the design of personalized treatment of COVID-19 patients suffering from DM as comorbidity.

Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions.

Despite the association of prevalent health conditions with coronavirus disease 2019 (COVID-19) severity, the disease-modifying biomolecules and their pathogenetic mechanisms remain unclear. This study aimed to understand the influences of COVID-19 on different comorbidities and vice versa through network-based gene expression analyses. Using the shared dysregulated genes, we identified key genetic determinants and signaling pathways that may involve in their shared pathogenesis. The COVID-19 showed significant upregulation of 93 genes and downregulation of 15 genes. Interestingly, it shares 28, 17, 6 and 7 genes with diabetes mellitus (DM), lung cancer (LC), myocardial infarction and hypertension, respectively. Importantly, COVID-19 shared three upregulated genes (i.e. MX2, IRF7 and ADAM8) with DM and LC. Conversely, downregulation of two genes (i.e. PPARGC1A and METTL7A) was found in COVID-19 and LC. Besides, most of the shared pathways were related to inflammatory responses. Furthermore, we identified six potential biomarkers and several important regulatory factors, e.g. transcription factors and microRNAs, while notable drug candidates included captopril, rilonacept and canakinumab. Moreover, prognostic analysis suggests concomitant COVID-19 may result in poor outcome of LC patients. This study provides the molecular basis and routes of the COVID-19 progression due to comorbidities. We believe these findings might be useful to further understand the intricate association of these diseases as well as for the therapeutic development.

Immune Interaction Map of Human SARS-CoV-2 Target Genes: Implications for Therapeutic Avenues.

There exists increasing evidence that people with preceding medical conditions, such as diabetes and cancer, have a higher risk of infection with SARS-CoV-2 and are more vulnerable to severe disease. To get insights into the possible role of the immune system upon COVID-19 infection, 2811 genes of the gene ontology term "immune system process GO: 0002376" were selected for coexpression analysis of the human targets of SARS-CoV-2 (HT-SARS-CoV-2) ACE2, TMPRSS2, and FURIN in tissue samples from patients with cancer and diabetes mellitus. The network between HT-SARS-CoV-2 and immune system process genes was analyzed based on functional protein associations using STRING. In addition, STITCH was employed to determine druggable targets. DPP4 was the only immune system process gene, which was coexpressed with the three HT-SARS-CoV-2 genes, while eight other immune genes were at least coexpressed with two HT-SARS-CoV-2 genes. STRING analysis between immune and HT-SARS-CoV-2 genes plotted 19 associations of which there were eight common networking genes in mixed healthy (323) and pan-cancer (11003) tissues in addition to normal (87), cancer (90), and diabetic (128) pancreatic tissues. Using this approach, three commonly applicable druggable connections between HT-SARS-CoV-2 and immune system process genes were identified. These include positive associations of ACE2-DPP4 and TMPRSS2-SRC as well as a negative association of FURIN with ADAM17. Furthermore, 16 drugs were extracted from STITCH (score <0.8) with 32 target genes. Thus, an immunological network associated with HT-SARS-CoV-2 using bioinformatics tools was identified leading to novel therapeutic opportunities for COVID-19.

Environmental pollution and COVID-19: the molecular terms and predominant disease outcomes of their sweetheart agreement.

As the Coronavirus situation (COVID-19) continues to evolve, many questions concerning the factors relating to the diffusion and severity of the disease remain unanswered.Whilst opinions regarding the weight of evidence for these risk factors, and the studies published so far are often inconclusive or offer contrasting results, the role of comorbidities in the risk of serious adverse outcomes in patients affected with COVID-19 appears to be evident since the outset. Hypertension, diabetes, and obesity are under discussion as important factors affecting the severity of disease. Air pollution has been considered to play a role in the diffusion of the virus, in the propagation of the contagion, in the severity of symptoms, and in the poor prognosis. Accumulating evidence supports the hypothesis that environmental particulate matter (PM) can trigger inflammatory responses at molecular, cellular, and organ levels, sustaining respiratory, cardiovascular, and dysmetabolic diseases.To better understand the intricate relationships among pre-existing conditions, PM, and viral infection, we examined the response at the molecular level of T47D human breast adenocarcinoma cells exposed to different fractions of PM. T47D cells express several receptors, including the aryl hydrocarbon receptor (AhR), and ACE2, the main - but not the only - receptor for SARS-CoV-2 entry.PM samples were collected in an urban background site located in the Northern area of the City of Bologna (Emilia-Romagna Region, Northern Italy) during winter 2013. T47D cells were exposed to organic or aqueous (inorganic) extracts at the final concentration of 8 m3 for a 4-hour duration. Both the concentration and the exposure time were chosen to resemble an average outdoor exposure. RNA was extracted from cells, purified and hybridised on 66k microarray slides from Agilent.The lists of differentially expressed genes in PM organic extracts were evaluated by using Metacore, and an enrichment analysis was performed to identify pathways maps, process networks, and disease by biomarkers altered after T47D treatment.The analysis of the modulated genes gave evidence for the involvement of PM in dysmetabolic diseases, including diabetes and obesity, and hypertension through the activation of the aryl hydrocarbon receptor (AhR) canonical pathway.On the basis of current knowledge, existing data, and exploratory experimental evidence, we tease out the likely molecular interplay that can ultimately tip the disease outcome into severity. Looking beyond ACE2, several additional key markers are identified. Disruption of these targets worsens pre-existing conditions and/or exacerbates the adverse effects induced by SARS-CoV-2 infection. Whilst appropriately designed, epidemiological studies are very much needed to investigate these associations based on our hypothesis of investigation, by reviewing recent experimental and epidemiological evidence, here we speculate and provide new insights on the possible role of environmental pollution in the exacerbation of effects by SARS-CoV-2 and other respiratory viruses. This work is intended to assist in the development of appropriate investigative approaches to protect public health.

Downregulation of microRNA-146a in diabetes, obesity and hypertension may contribute to severe COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is able to produce an excessive host immune reaction and may leads to severe disease- a life-threatening condition occurring more often in patients suffering from comorbidities such as hypertension, diabetes and obesity. Infection by human corona viruses highly depends on host microRNA (miR) involved in regulation of host innate immune response and inflammation-modulatory miR-146a is among the first miRs induced by immune reaction to a virus. Moreover, recent analysis showed that miR-146 is predicted to target at the SARS-CoV-2 genome. As the dominant regulator of Toll-like receptors (TLRs) downstream signaling, miR-146a may limit excessive inflammatory response to virus. Downregulation of circulating miR-146a was found in diabetes, obesity and hypertension and it is reflected by enhanced inflammation and fibrosis, systemic effects accompanying severe COVID-19. Thus it could be hypothesized that miR-146a deficiency may contribute to severe COVID-19 state observed in diabetes, obesity and hypertension but further investigations are needed.

Investigation of COVID-19 comorbidities reveals genes and pathways coincident with the SARS-CoV-2 viral disease.

The emergence of the SARS-CoV-2 virus and subsequent COVID-19 pandemic initiated intense research into the mechanisms of action for this virus. It was quickly noted that COVID-19 presents more seriously in conjunction with other human disease conditions such as hypertension, diabetes, and lung diseases. We conducted a bioinformatics analysis of COVID-19 comorbidity-associated gene sets, identifying genes and pathways shared among the comorbidities, and evaluated current knowledge about these genes and pathways as related to current information about SARS-CoV-2 infection. We performed our analysis using GeneWeaver (GW), Reactome, and several biomedical ontologies to represent and compare common COVID-19 comorbidities. Phenotypic analysis of shared genes revealed significant enrichment for immune system phenotypes and for cardiovascular-related phenotypes, which might point to alleles and phenotypes in mouse models that could be evaluated for clues to COVID-19 severity. Through pathway analysis, we identified enriched pathways shared by comorbidity datasets and datasets associated with SARS-CoV-2 infection.

An Assessment on Impact of COVID-19 Infection in a Gender Specific Manner.

Coronavirus disease 2019 (COVID-19) is caused by novel coronavirus Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first time reported in December 2019 in Wuhan, China and thereafter quickly spread across the globe. Till September 19, 2020, COVID-19 has spread to 216 countries and territories. Severe infection of SARS-CoV-2 cause extreme increase in inflammatory chemokines and cytokines that may lead to multi-organ damage and respiratory failure. Currently, no specific treatment and authorized vaccines are available for its treatment. Renin angiotensin system holds a promising role in human physiological system specifically in regulation of blood pressure and electrolyte and fluid balance. SARS-CoV-2 interacts with Renin angiotensin system by utilizing angiotensin-converting enzyme 2 (ACE2) as a receptor for its cellular entry. This interaction hampers the protective action of ACE2 in the cells and causes injuries to organs due to persistent angiotensin II (Ang-II) level. Patients with certain comorbidities like hypertension, diabetes, and cardiovascular disease are under the high risk of COVID-19 infection and mortality. Moreover, evidence obtained from several reports also suggests higher susceptibility of male patients for COVID-19 mortality and other acute viral infections compared to females. Analysis of severe acute respiratory syndrome coronavirus (SARS) and Middle East respiratory syndrome coronavirus (MERS) epidemiological data also indicate a gender-based preference in disease consequences. The current review addresses the possible mechanisms responsible for higher COVID-19 mortality among male patients. The major underlying aspects that was looked into includes smoking, genetic factors, and the impact of reproductive hormones on immune systems and inflammatory responses. Detailed investigations of this gender disparity could provide insight into the development of patient tailored therapeutic approach which would be helpful in improving the poor outcomes of COVID-19. Graphical abstract.

Practicing precision medicine with intelligently integrative clinical and multi-omics data analysis.

Precision medicine aims to empower clinicians to predict the most appropriate course of action for patients with complex diseases like cancer, diabetes, cardiomyopathy, and COVID-19. With a progressive interpretation of the clinical, molecular, and genomic factors at play in diseases, more effective and personalized medical treatments are anticipated for many disorders. Understanding patient's metabolomics and genetic make-up in conjunction with clinical data will significantly lead to determining predisposition, diagnostic, prognostic, and predictive biomarkers and paths ultimately providing optimal and personalized care for diverse, and targeted chronic and acute diseases. In clinical settings, we need to timely model clinical and multi-omics data to find statistical patterns across millions of features to identify underlying biologic pathways, modifiable risk factors, and actionable information that support early detection and prevention of complex disorders, and development of new therapies for better patient care. It is important to calculate quantitative phenotype measurements, evaluate variants in unique genes and interpret using ACMG guidelines, find frequency of pathogenic and likely pathogenic variants without disease indicators, and observe autosomal recessive carriers with a phenotype manifestation in metabolome. Next, ensuring security to reconcile noise, we need to build and train machine-learning prognostic models to meaningfully process multisource heterogeneous data to identify high-risk rare variants and make medically relevant predictions. The goal, today, is to facilitate implementation of mainstream precision medicine to improve the traditional symptom-driven practice of medicine, and allow earlier interventions using predictive diagnostics and tailoring better-personalized treatments. We strongly recommend automated implementation of cutting-edge technologies, utilizing machine learning (ML) and artificial intelligence (AI) approaches for the multimodal data aggregation, multifactor examination, development of knowledgebase of clinical predictors for decision support, and best strategies for dealing with relevant ethical issues.

Clinical Study of Hyperglycemia and SARS-CoV-2 Infection in Intensive Care Unit Patients.

BACKGROUND/AIM: Reports indicate that coronaviridae may inhibit insulin secretion. In this report we aimed to describe the course of glycemia in critically ill patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. PATIENTS AND METHODS: We studied 36 SARS-CoV-2 patients (with no history of diabetes) in one intensive care unit (ICU). All the patients were admitted for hypoxemic respiratory failure; all but four required mechanical ventilation. The mean (±SD) age of the patients was 64.7 (9.7) years; 27 were men; the mean (±SD) duration of ICU stay was 12.9 (8.3 days). RESULTS: Twenty of 36 patients presented with hyperglycemia; brief intravenous infusions of short-acting insulin were administered in six patients. As of May 29 2020, 11 patients had died (seven with hyperglycemia). In 17 patients the Hyperglycemia Index [HGI; defined as the area under the curve of (hyper)glycemia level*time (h) divided by the total time in the ICU] was <16.21 mg/dl (0.90 mmol/l), whereas in three patients the HGI was ≥16.21 mg/dl (0.90 mol/l) and <32.25 mg/dl (1.79 mmol/l). CONCLUSION: In our series of ICU patients with SARS-CoV-2 infection, and no history of diabetes, a substantial number of patients had hyperglycemia, to a higher degree than would be expected by the stress of critical illness, lending credence to reports that speculated a tentative association between SARS-CoV-2 and hyperglycemia. This finding is important, since hyperglycemia can lead to further infectious complications.

Role of comorbidities like diabetes on severe acute respiratory syndrome coronavirus-2: A review.

Pandemic coronavirus disease-2019, commonly known as COVID-19 caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a highly contagious disease with a high mortality rate. Various comorbidities and their associated symptoms accompany SARS-CoV-2 infection. Among the various comorbidities like hypertension, cardiovascular disease and chronic obstructive pulmonary disease, diabetes considered as one of the critical comorbidity, which could affect the survival of infected patients. The severity of COVID-19 disease intensifies in patients with elevated glucose level probably via amplified pro-inflammatory cytokine response, poor innate immunity and downregulated angiotensin-converting enzyme 2. Thus, the use of ACE inhibitors or angiotensin receptor blockers could worsen the glucose level in patients suffering from novel coronavirus infection. It also observed that the direct ß-cell damage caused by virus, hypokalemia and cytokine and fetuin-A mediated increase in insulin resistance could also deteriorate the diabetic condition in COVID-19 patients. This review highlights the current scenario of coronavirus disease in pre-existing diabetic patients, epidemiology, molecular perception, investigations, treatment and management of COVID-19 disease in patients with pre-existing diabetes. Along with this, we have also discussed unexplored therapies and future perspectives for coronavirus infection.