Metabolomics in Depression: What We Learn from Preclinical and Clinical Evidences.

Depression is one of the predominant common mental illnesses that affects millions of people of all ages worldwide. Random mood changes, loss of interest in routine activities, and prevalent unpleasant senses often characterize this common depreciated mental illness. Subjects with depressive disorders have a likelihood of developing cardiovascular complications, diabesity, and stroke. The exact genesis and pathogenesis of this disease are still questionable. A significant proportion of subjects with clinical depression display inadequate response to antidepressant therapies. Hence, clinicians often face challenges in predicting the treatment response. Emerging reports have indicated the association of depression with metabolic alterations. Metabolomics is one of the promising approaches that can offer fresh perspectives into the diagnosis, treatment, and prognosis of depression at the metabolic level. Despite numerous studies exploring metabolite profiles post-pharmacological interventions, a quantitative understanding of consistently altered metabolites is not yet established. The article gives a brief discussion on different biomarkers in depression and the degree to which biomarkers can improve treatment outcomes. In this review article, we have systemically reviewed the role of metabolomics in depression along with current challenges and future perspectives.

Safety and Efficacy of Calcitonin Gene-related Peptide Receptor Antagonists and Selective Serotonin Receptor Agonist in the Management of Migraine: A Systematic Review and Meta-analysis.

BACKGROUND: Recently, US Food and Drug Administration (FDA) has approved calcitonin gene-related peptide receptor antagonists (rimegepant, and ubrogepant), and selective serotonin receptor agonists (lasmiditan) in the management of migraine. However, the exact safety and efficacy profile of these drugs is unclear so far. METHODS: The study's primary objective was to determine the exact safety and efficacy profile. The overall estimate was calculated in terms of risk ratios using a suitable model. The subgroup analysis was also performed to check the effect of individual drugs on the outcome, whereas sensitivity analysis was performed to check the effects of outliers on the outcome. All the analyses were performed using Rev Man 5. The drugs have shown significant improvement in efficacy parameters (pain freedom, most bothersome symptoms, phonophobia, nausea, and photophobia). RESULTS: The subgroup analysis results have shown significant improvement in all efficacy parameters in the rimegepant and ubrogepant groups. The effect of ubrogepant on safety parameters was found to be non-significant, indicating a better safety profile of ubrogepant than lasmiditan. CONCLUSION: The sensitivity analysis results have shown no effect of outliers on the efficacy parameters. Based on the available evidence, recently approved drugs are effective in the treatment of migraine, however, associated with few adverse drug reactions.

Repurposing of drugs against bacterial infections: A pharmacovigilance-based data mining approach.

The World Health Organization (WHO) has published a list of priority pathogens that urgently require research to develop new antibiotics. The main aim of the current study is to identify potential marketed drugs that can be repurposed against bacterial infections. A pharmacovigilance-based drug repurposing approach was used to identify potential drugs. OpenVigil 2.1 tool was used to query the FDA Adverse Event Reporting System database. The reporting odds ratio (ROR) < 1, ROR95CI upper bound <1, and no. of cases ≥30 were used for filtering and sorting of drugs. Sunburst plot was used to represent drugs in a hierarchical order using the Anatomical Therapeutic Chemical classification. Molecular docking and dynamics were performed using the Maestro and Desmond modules of Schrodinger 2023 software respectively. A total of 40 drugs with different classes were identified based on the pharmacovigilance approach which has antibacterial potential. The molecular docking results have shown energetically favored binding conformation of lisinopril against 3-deoxy-manno-octulosonate cytidylyltransferase, UDP-2,3-diacylglucosamine hydrolase, and penicillin-binding protein 3 (PBP3) of Pseudomonas aeruginosa; olmesartan, atorvastatin against lipoteichoic acids flippase LtaA and rosiglitazone and varenicline against  d-alanine ligase of Staphylococcus aureus; valsartan against peptidoglycan deacetylase (SpPgdA) and atorvastatin against CDP-activated ribitol for teichoic acid precursors of Streptococcus pneumoniae. Further, molecular dynamic results have shown the stability of identified drugs in the active site of bacterial targets except lisinopril with PBP3. Lisinopril, olmesartan, atorvastatin, rosiglitazone, varenicline, and valsartan have been identified as potential drugs for repurposing against bacterial infection.

High annualized bleeding rates in pediatric patients with inherited platelet function disorders.

Not available.

Role of Network Pharmacology in Prediction of Mechanism of Neuroprotective Compounds.

Network pharmacology is an emerging pioneering approach in the drug discovery process, which is used to predict the therapeutic mechanism of compounds using various bioinformatic tools and databases. Emerging studies have indicated the use of network pharmacological approaches in various research fields, particularly in the identification of possible mechanisms of herbal compounds/ayurvedic formulations in the management of various diseases. These techniques could also play an important role in the prediction of the possible mechanisms of neuroprotective compounds. The first part of the chapter includes an introduction on neuroprotective compounds based on literature. Further, network pharmacological approaches are briefly discussed. The use of network pharmacology in the prediction of the neuroprotective mechanism of compounds is discussed in detail with suitable examples. Finally, the chapter concludes with the current challenges and future prospectives.

Assessment of rare bleeding disorders in adolescents with heavy menstrual bleeding.

INTRODUCTION: There are a significant number of patients with mucocutaneous bleeding, specifically heavy menstrual bleeding (HMB), who do not have a diagnosed bleeding disorder. These patients receive nontargeted interventions and may have suboptimal treatments. Functional assays, particularly for fibrinolytic and rare platelet function defects, are not robust and not readily available. AIM: We aimed to prospectively evaluate the prevalence of genetic defects associated with rare bleeding disorders and describe alterations of coagulation and fibrinolysis in a cohort of adolescents with HMB. METHODS: We performed a prospective observational cohort study of patients with HMB and unexplained bleeding. The study utilized a next generation sequencing panel and investigational global assays of coagulation and fibrinolysis. Additionally, specific functional assays were performed to help characterize novel variants that were identified. RESULTS: In 10 of the 17 patients (∼59%), genetic variants were identified on molecular testing. Thrombin generation by calibrated thromboelastography was not significantly altered in this patient population. The clot formation and lysis assay showed a trend towards increased fibrinolysis with rapid phase of decline in 23% of the patients. Further corresponding functional assays and study population are described. CONCLUSION: Our study describes a unique correlative model in a homogenous cohort of patients with HMB and unexplained bleeding which may inform future diagnostic algorithms, genotype-phenotype correlations as well as aid in specific targeted treatment approaches. Larger future studies may inform risk stratification of patients and improve health related outcomes in patients with HMB.

Identification of novel signal of Raynaud's phenomenon with Calcitonin Gene-Related Peptide(CGRP) antagonists using data mining algorithms and network pharmacological approaches.

BACKGROUND: Calcitonin gene-related peptide (CGRP) antagonists are recently approved for the treatment of migraine. AIM: The main aim of the current study was to find out the association of CGRP antagonists with RP using data mining algorithms integrated with network pharmacological approaches. RESEARCH DESIGN AND METHODS: The individual case safety reports were extracted using OpenVigil2.1-MedDRA-V17 (2004Q1-2022Q3), the United States Adverse Event Reporting System (US FAERS). The data mining algorithms i.e. reporting odds ratio (ROR) with 95% confidence and proportionality reporting ratio (PRR) with associated chi-square value were calculated along with a minimum of three ICSRs to identify the signal. Further, the network was constructed using Cytoscape 3.7.2. Finally, molecular docking was performed using Glide, Schrodinger Inc. RESULTS: The PRR ≥2 with a linked chi-square value ≥4, add up of co-occurrence ≥3, and a lower limit of 95% confidence interval of ROR exceeding 2 indicates a positive signal of RP. Further, the network pharmacological and molecular docking results have shown the involvement of insulin-like growth factor 1-receptor (IGF1R) pathways. CONCLUSION: The RP is recognized as a novel signal with all CGRP antagonists.

Optimization of laboratory diagnosis of heparin-induced thrombocytopenia using HemosIL-AcuStar-HIT-IgG assay.

OBJECTIVE: The aim of this study was to determine an optimal cutoff value for the newly available HemosIL-AcuStar-HIT-IgG assay (AcuStar) for the diagnosis of heparin-induced thrombocytopenia (HIT). METHOD: We evaluated the performance of AcuStar using serotonin release assay (SRA) as the gold standard and incorporated 4T score calculation in a cohort of suspected HIT cases. Statistical analysis was performed to determine optimal cutoff value for the diagnosis of HIT. RESULT: A diagnosis of HIT can be excluded with a platelet factor 4 (PF4) value of <0.4 U/mL by AcuStar and 4T score in the low-risk category (≤3). All other cases will require confirmation with a functional test. CONCLUSION: Our study resulted in the implementation of a diagnostic algorithm for laboratory diagnosis of HIT, which incorporates pretest calculation of 4T score and AcuStar as a screening test, with reflex confirmation by SRA. This new algorithm resulted in extended hours of test availability and a more rapid turnaround time in reporting PF4 results.

Association of temozolomide with progressive multifocal leukoencephalopathy: a disproportionality analysis integrated with network pharmacology.

BACKGROUND: Temozolomide (TMZ) is an alkylating agent approved for the management of glioblastoma. The TMZ is not known for progressive multifocal leukoencephalopathy (PML). The main objective of the current study is to find out the association of TMZ with PML using disproportionality analysis of FDA Adverse Event Reporting System (FAERS) data integrated with network pharmacological approaches. RESEARCH DESIGN AND METHODS: OpenVigil tool was used to query the FAERS database. The disproportionality measures were calculated. The network has been constructed using Cytoscape. Finally, the possible binding interactions were studied using Glide, Schrödinger Inc. RESULTS: A total number of 3502 cases of PML were reported in the FAERS database. Out of these, 10 cases were found with TMZ. The subgroup analysis results have shown a greater number of cases in females. The network has indicated the involvement of human mitogen-activated protein kinase, 3-phosphoinositide-dependent protein kinase 1 protein, human mTOR complex protein, phosphatidylinositol 4,5-bisphosphate 3-kinase protein, and glycogen synthase kinase-3 beta protein. The docking results have indicated good interactions of TMZ with active site of glycogen synthase kinase-3 beta and mitogen-activated protein kinase 1 as compared to other identified targets. CONCLUSION: The PML is identified as novel signal with temozolomide.

Association of Cardiovascular Events with COVID-19 Vaccines using Vaccine Adverse Event Reporting System (VAERS): A Retrospective Study.

BACKGROUND: COVID-19 vaccines have played a crucial role in reducing the burden of the global pandemic. However, recent case reports have indicated the association of the COVID- 19 vaccines with cardiovascular events but the exact association is unclear so far. OBJECTIVE: Therefore, the objective of the current study is to find out the association of cardiovascular events with COVID-19 vaccines. METHODS: The COVID-19 Vaccine Knowledge Base (Cov19VaxKB) tool was used to query the Vaccine Adverse Event Reporting System (VAERS) database. The proportional reporting ratio [PRR (≥2)] with associated chi-squared value (>4), and the number of cases > 0.2% of total reports, was used to assess the association of COVID-19 vaccines with cardiovascular events. RESULTS: A total of 33,754 cases of cardiovascular events associated with COVID-19 vaccines were found in the Cov19VaxKB tool. The cases were observed in different age groups (18-64, and 65 years and above) and gender. The disproportionality measures indicate a statistically significant association between cardiovascular events and COVID-19 vaccines. CONCLUSION: The current study identified a signal of various cardiovascular events with the COVID-19 vaccines. However, further causality assessment is required to confirm the association.

Implementation of a Bleeding Risk Screening Tool and Hematology Referral Process Prior to Pediatric Endoscopy.

OBJECTIVES: Gastrointestinal (GI) endoscopic procedures are considered low risk with an overall bleeding risk for upper and lower endoscopies of 0.11%. However, a certain population of patients may have a higher risk for bleeding, and there is not a standardized process for screening patients to determine who these patients are. METHODS: At Children's Wisconsin, our gastroenterology and hematology divisions adapted an abbreviated version of a validated, history-based bleeding risk screening tool and implemented a hematology referral process to identify those at risk for bleeding prior to their first endoscopy. Provider compliance with the bleeding screen, referral to hematology, time to be seen in hematology clinic, new diagnoses of bleeding disorders, and bleeding complications were assessed from 2019 to 2021 across 3 phases. RESULTS: Provider compliance with the bleeding screen improved throughout our study from 48% (120/251) to 75% (189/253). For those who screened positive, compliance with referral to hematology ranged from 38% to 74% across our phases. The overall time to be seen by hematology decreased from 30 days to 7.5 days. Eighteen patients ultimately screened positive and were seen in hematology clinic, of whom 22% (4/18) were diagnosed with a new bleeding disorder. No bleeding complications were seen in our study population. CONCLUSIONS: Our quality improvement project provided a standardized screening tool to assess preoperative bleeding risk and reinforced the value of a history-based screening tool. This modified screening tool identified those with an undiagnosed bleeding disorder and preventative measures were undertaken to prevent procedural bleeding complications.

Consensus report on flow cytometry for platelet function testing in thrombocytopenic patients: communication from the SSC of the ISTH.

BACKGROUND: Platelet count alone does not reliably predict bleeding risk, suggesting platelet function is important to monitor in patients with thrombocytopenia. There is still an unmet need for improved platelet function diagnostics in patients with low platelet count in many clinical situations. Flow cytometry is a promising tool allowing reliable platelet function study in this setting. OBJECTIVES: The goal of this joint project between the International Society on Thrombosis and Haemostasis (ISTH) Scientific Standardization Committee (SSC) Subcommittees on Platelet Physiology and Platelet Immunology is to provide expert consensus guidance on the use of flow cytometry for the evaluation of platelet function, particularly activation, in patients with low platelet counts. METHODS: A literature review was performed to identify relevant questions and areas of interest. An electronic expression of interest form was thereafter announced on the ISTH webpage, followed by a survey encompassing 37 issues regarding preanalytical, analytical, postanalytical, and performance aspects. Areas of disagreement or uncertainty were identified and formed the basis for 2 focus group discussions. RESULTS: Consensus recommendations relative to patient sample collection, preanalytical variables, sample type, platelet-count cutoff, any potential specific modification of the standard flow cytometry protocol, and results expression and reporting are proposed based on the current practices of experts in the field as well as on literature review. CONCLUSION: The proposed consensus recommendations would allow standardization of protocols in upcoming clinical studies. The clinical utility of platelet function testing using flow cytometry to predict bleeding risk still needs rigorous multicenter outcome studies in patients with thrombocytopenia.

HLA antibodies in fetal and neonatal alloimmune thrombocytopenia.

BACKGROUND: Fetal and neonatal alloimmune thrombocytopenia (FNAIT) is caused by antibodies against human platelet antigens (HPA). However, in many cases that meet clinical criteria for the condition, maternal sera do not have HPA antibodies. In studies examining whether human leukocyte antigen (HLA) antibodies cause FNAIT, the results are limited and inconclusive. This study sought to examine whether clinically suspected FNAIT cases with absent maternal HPA antibodies had different HLA antibody strength and specificity compared to controls. STUDY DESIGN AND METHODS: A retrospective case-control study assessed class I HLA antibody strength and specificity in cases submitted for testing to Versiti, Wisconsin. There were 813 cases that met initial screening criteria, but written consent could only be obtained for 50. After review of medical records and expert panel review, 31 cases with clinical criteria of FNAIT and maternal HLA but not HPA antibodies were included. Each case was matched for maternal age, gestational age at delivery, parity, and race/ethnicity to two controls from unaffected pregnancies that had maternal serum HLA antibodies. RESULTS: FNAIT cases were found to have both significantly higher HLA antibody strength, measured by mean fluorescence index (MFI), and broader HLA antibody specificity at antigen epitope level, compared to matched controls (p < .001). p-values remained significant after controlling for parity and gestational age at delivery. DISCUSSION: Additional studies are needed to further examine whether the strong HLA antibodies identified in HPA-antibody-negative cases directly cause neonatal thrombocytopenia and whether prenatal treatment may be warranted in select cases to prevent recurrence.

Association of antiviral drugs and their possible mechanisms with DRESS syndrome using data mining algorithms.

Antiviral drugs are not known for drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome. The current study aims is to find out the association of antiviral drugs and their possible mechanism with DRESS. Data mining algorithms such as proportional reporting ratio that is, PRR (≥2) with associated χ2  value (>4), reporting odds ratio that is, ROR (≥2) with 95% confidence interval and case count (≥3) were calculated to identify a possible signal. Further, molecular docking studies were conducted to check the interaction of selected antiviral drugs with possible targets. The potential signal of DRESS was found to be associated with abacavir, acyclovir, ganciclovir, lamivudine, lopinavir, nevirapine, ribavirin, ritonavir, and zidovudine among all selected antiviral drugs. Further, subgroup analysis has also shown a potential signal in different age groups and gender. The sensitivity analysis results have shown a decrease in the strength of the signal, however, there was no significant impact on the outcome except for acyclovir. The docking results have indicated the possible involvement of human leukocyte antigen (HLA)*B1502 and HLA*B5801. The positive signal of DRESS was found with selected antiviral drugs except for acyclovir.

Drugs acting on the renin-angiotensin-aldosterone system (RAAS) and deaths of COVID-19 patients: a systematic review and meta-analysis of observational studies.

BACKGROUND: Angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARBs) are two of the most commonly used antihypertensive drugs acting on the renin-angiotensin-aldosterone system (RAAS). Previous research has shown that RAAS inhibitors increase the expression of angiotensin-converting enzyme, a cellular receptor for the severe acute respiratory syndrome coronavirus 2, raising concerns that the use of ACEi and ARBs in hypertensive patients may increase COVID-19 patient mortality. Therefore, the main aim of the current study was to find out the role of drugs acting on RAAS, particularly ACEi/ARBs in the deaths of COVID-19 patients. RESULTS: In total, 68 studies were found to be appropriate, reporting a total of 128,078 subjects. The odds ratio was found to be 1.14 [0.95, 1.36], which indicates the non-significant association of ACEi/ARBs with mortality of COVID-19 patients. Further, the association of individual ACEi/ARBs with mortality of COVID-19 patients was also found non-significant. The sensitivity analysis results have shown no significant effect of outliers on the outcome. CONCLUSIONS: Based on available evidence, ACEi/ARB were not significantly associated with deaths of COVID-19 patients.

Next-generation sequencing in the biodiversity conservation of endangered medicinal plants.

Medicinal plants have been used as traditional herbal medicines in the treatment of various types of diseases. However, the increased demand for these plants highlights the importance of conservation specifically for endangered species. Significant advancements in next-generation sequencing (NGS) technologies have accelerated medicinal plant research while reducing costs and time demands. NGS systems enable high-throughput whole genome sequencing as well as direct RNA sequencing and transcriptome analysis. The sequence data sets created can be used in a variety of areas of study, including biodiversity conservation, comparative genomics, transcriptomic analysis, single cell mining, metagenomics, epigenetics, molecular marker discovery, multi genome sequencing, and so on. Commercial sequencing service providers are constantly working to improve technologies to address bioinformatics problems in NGS data analysis. Several genome sequencing projects on medicinal plants have been completed recently and a few more are in the works. In some medicinal plants, massive NGS-based data has been developed. In the present review, we have attempted to briefly discuss advancements in NGS technology on medicinally essential plants in India. The review will also provide ideas for applying NGS technologies for exploring genomes of various endangered medicinal plants whose genome sequences are not normally available and thus provides valuable insights for the conservation of these vulnerable species.

Identification of vaccine candidate against Omicron variant of SARS-CoV-2 using immunoinformatic approaches.

Despite the availability of COVID-19 vaccines, additional more potent vaccines are still required against the emerging variations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the present investigation, we have identified a promising vaccine candidate against the Omicron (B.1.1.529) using immunoinformatics approaches. Various available tools like, the Immune Epitope Database server resource, and NetCTL-1.2, have been used for the identification of the promising T-cell and B-cell epitopes. The molecular docking was performed to check the interaction of TLR-3 receptors and validated 3D model of vaccine candidate. The codon optimization was done followed by cloning using SnapGene. Finally, In-silico immune simulation profile was also checked. The identified T-cell and B-cell epitopes have been selected based on their antigenicity (VaxiJen v2.0) and, allergenicity (AllerTOP v2.0). The identified epitopes with antigenic and non-allergenic properties were fused with the specific peptide linkers. In addition, the 3D model was constructed by the PHYRE2 server and validated using ProSA-web. The validated 3D model was further docked with the Toll-like receptor 3 (TLR3) and showed good interaction with the amino acids which indicate a promising vaccine candidate against the Omicron variant of SARS-CoV-2. Finally, the codon optimization, In-silico cloning and immune simulation profile was found to be satisfactory. Overall, the designed vaccine candidate has a potential against variant of SARS-Cov-2. However, further experimental studies are required to confirm.

RNA-Seq Analysis of Developing Grains of Wheat to Intrigue Into the Complex Molecular Mechanism of the Heat Stress Response.

Heat stress is one of the significant constraints affecting wheat production worldwide. To ensure food security for ever-increasing world population, improving wheat for heat stress tolerance is needed in the presently drifting climatic conditions. At the molecular level, heat stress tolerance in wheat is governed by a complex interplay of various heat stress-associated genes. We used a comparative transcriptome sequencing approach to study the effect of heat stress (5°C above ambient threshold temperature of 20°C) during grain filling stages in wheat genotype K7903 (Halna). At 7 DPA (days post-anthesis), heat stress treatment was given at four stages: 0, 24, 48, and 120 h. In total, 115,656 wheat genes were identified, including 309 differentially expressed genes (DEGs) involved in many critical processes, such as signal transduction, starch synthetic pathway, antioxidant pathway, and heat stress-responsive conserved and uncharacterized putative genes that play an essential role in maintaining the grain filling rate at the high temperature. A total of 98,412 Simple Sequences Repeats (SSR) were identified from de novo transcriptome assembly of wheat and validated. The miRNA target prediction from differential expressed genes was performed by psRNATarget server against 119 mature miRNA. Further, 107,107 variants including 80,936 Single nucleotide polymorphism (SNPs) and 26,171 insertion/deletion (Indels) were also identified in de novo transcriptome assembly of wheat and wheat genome Ensembl version 31. The present study enriches our understanding of known heat response mechanisms during the grain filling stage supported by discovery of novel transcripts, microsatellite markers, putative miRNA targets, and genetic variant. This enhances gene functions and regulators, paving the way for improved heat tolerance in wheat varieties, making them more suitable for production in the current climate change scenario.

The Value of Federated Data Networks in Oncology: What Research Questions Do They Answer? Outcomes From a Systematic Literature Review.

OBJECTIVES: Real-world evidence (RWE) plays an important role in addressing key research questions of interest to healthcare decision makers. Federated data networks (FDNs) apply novel technology to enable the conduct of RWE studies with multiple partners, without the need to share the individual partner's data set. A systematic review of the published literature was performed to determine which types of research questions can best be addressed through FDNs, specifically in the field of oncology. METHODS: Systematic searches of MEDLINE and Embase were undertaken to identify the types of research questions that had been addressed in studies using FDNs. Additional information was retrieved about study characteristics, statistical methods, and the FDN itself. RESULTS: In total, 40 publications were included where research questions on the following had been addressed (multiple categories possible): disease natural history (58%), safety surveillance (18%), treatment pathways (15%), comparative effectiveness (10%), and cost/resource use studies (3%)-13% of studies had to be left uncategorized. A total of 50% of the studies were run with data partners in networks of ≤5. The size of the networks ranged from 227 patients to >5 million patients. Statistical methods used included distributed learning and distributed regression methods. CONCLUSIONS: Further work is needed to raise awareness of the important role that FDNs can play in leveraging readily available RWE to address key research questions of interest in cancer and the benefits to the research community in engaging in federated data initiatives with a long-term perspective.