Anti-CD4 antibody and dendrimeric peptide based targeted nano-liposomal dual drug formulation for the treatment of HIV infection.

AIMS: Development and characterization of LAM and DTG loaded liposomes conjugated anti-CD4 antibody and peptide dendrimer (PD2) to improve the therapeutic efficacy and to achieve targeted treatment for HIV infection. MAIN METHODS: A 2-level full factorial design was used to optimize the preparation of dual drug loaded liposomes. Optimized dual drug loaded ligand conjugated liposomes were assessed for their cytotoxicity and cell internalization on TZM-bl cells. Anti-HIV efficiency of the dual drug loaded liposomes were screened for their inhibitory potential in TZM-bl cells and the activities were confirmed using Peripheral Blood Mononuclear Cells (PBMCs). KEY FINDINGS: The particle size of the optimized dual drug-loaded liposomes was 133.7 ± 4.04 nm, and the spherical morphology of the liposomes was confirmed by TEM analysis. The entrapment efficiency was 34 ± 4.9 % and 54 ± 1.8 % for LAM and DTG, respectively, and a slower in vitro release of LAM and DTG was observed when entrapped into liposomes. The cytotoxicity of the dual drug loaded liposomes was similar to the cytotoxicity of free drug solutions. Conjugation of anti-CD4 antibody and PD2 did not significantly influence the cytotoxicity but it enhanced the uptake of liposomes into the cells. Conjugated dual drug loaded liposomes exhibited better HIV inhibition with lower IC50 values (0.0003 ± 0.0002 µg/mL) compared to their free drug solutions (0.002 ± 0.001 µg/mL). The liposomal formulations have shown similar activities in both screening and confirmatory cell-based assays. SIGNIFICANCE: The results demonstrated the cell targeting ability of dual drug loaded liposomes conjugated with anti-CD4 antibody and peptide dendrimer. Conjugated liposomes also improved anti-HIV efficiency of LAM and DTG.

Antibiotic-Dispensing Patterns and Awareness of Anti-microbial Resistance Among the Community Pharmacists in South-Central India.

Background Anti-microbial resistance (AMR) is an ongoing epidemic contributing to extremely high healthcare costs and hospital admissions. Inappropriate dispensing of antibiotics is one of the root causes of AMR. Hence, our study aimed to assess antibiotic-dispensing patterns and AMR awareness among pharmacists from South-Central India. Methodology This cross-sectional observational study was conducted over a period of two months from June to July 2023. The pharmacies in urban and semi-urban areas of coastal and central districts of the Indian state of Andhra Pradesh were surveyed. Data were collected using a predesigned questionnaire for antibiotic-dispensing patterns and awareness of AMR, as approved by the Institutional Ethics Committee of Aster Ramesh Hospital, Vijayawada, India. The data were collected and analyzed descriptively by cross-tabulation. Results Among the 389 pharmacies that responded, 78% (n = 303) were dispensing antibiotics over the counter (OTC) and 22% (n = 86) were dispensing antibiotics only for valid prescriptions. It was found that antibiotics were dispensed OTC for common ailments such as the common cold, cough, sore throat, nasal congestion, fever, diarrhea, and urinary tract infections. As per the World Health Organization-recommended Access, Watch, and Reserve (AWaRe) criterion, antibiotics under the Watch group such as macrolides (azithromycin), fluoroquinolones (ciprofloxacin, norfloxacin, levofloxacin, and ofloxacin) and third-generation cephalosporins (cefixime and cefpodoxime) were found to be widely dispensed OTC. The most common antibiotics dispensed OTC were azithromycin (54.1%), amoxicillin (47.5%), cefixime (40%), amoxicillin + clavulanic acid (15.2%), ofloxacin (13.5%), ciprofloxacin (10%), and doxycycline (6.6%). Among the OTC dispensers, 82.5% (n = 250) were unaware of AMR and 17.5% were partially aware. However, 57% (n = 49) were unaware of AMR and its effects, in pharmacies dispensing antibiotics for valid prescriptions. Conclusion Our findings aggregate evidence on the alarming trend of inappropriate antibiotic-dispensing patterns that may further exacerbate AMR. Strict regulatory enforcement and periodical monitoring to regulate antibiotic dispensing to control unethical dispensing are inevitably necessary.

Phytochemical characterization of Typha domingensis and the assessment of therapeutic potential using in vitro and in vivo biological activities and in silico studies.

Typha domingensis, a medicinal plant with significant traditional importance for curing various human diseases, has potentially bioactive compounds but was less explored previously. Therefore, this study aims to investigate the therapeutic potential of T. domingensis by evaluating the phytochemical profile through high-performance liquid chromatography (HPLC) techniques and its biological activities (in vitro and in vivo) from the methanolic extract derived from the entire plant (TDME). The secondary metabolite profile of TDME regulated by reverse phase ultra-high-performance liquid chromatography-mass spectrometry (RP-UHPLC-MS) revealed some bioactive compounds by -ve and +ve modes of ionization. The HPLC quantification study showed the precise quantity of polyphenols (p-coumaric acid, 207.47; gallic acid, 96.25; and kaempferol, 95.78 µg/g extract). The enzyme inhibition assays revealed the IC50 of TDME as 44.75 ± 0.51, 52.71 ± 0.01, and 67.19 ± 0.68 µgmL-1, which were significant compared to their respective standards (indomethacin, 18.03 ± 0.12; quercetin, 4.11 ± 0.01; and thiourea, 8.97 ± 0.11) for lipoxygenase, α-glucosidase, and urease, respectively. Safety was assessed by in vitro hemolysis (4.25% ± 0.16% compared to triton × 100, 93.51% ± 0.36%), which was further confirmed (up to 10 g/kg) by an in vivo model of rats. TDME demonstrated significant (p < 0.05) potential in analgesic activity by hot plate and tail immersion tests and anti-inflammatory activity by the carrageenan-induced hind paw edema model. Pain latency decreased significantly, and the anti-inflammatory effect increased in a dose-dependent way. Additionally, in silico molecular docking revealed that 1,3,4,5-tetracaffeoylquinic acid and formononetin 7-O-glucoside-6″-O-malonate possibly contribute to enzyme inhibitory activities due to their higher binding affinities compared to standard inhibitors. An in silico absorption, distribution, metabolism, excretion, and toxicological study also predicted the pharmacokinetics and safety of the chosen compounds identified from TDME. To sum up, it was shown that TDME contains bioactive chemicals and has strong biological activities. The current investigations on T. domingensis could be extended to explore its potential applications in nutraceutical industries and encourage the isolation of novel molecules with anti-inflammatory and analgesic effects.

Elucidation of genetic determinants of dyslipidaemia using a global screening array for the early detection of coronary artery disease.

Dyslipidemia is a major risk factor for the development of coronary artery disease (CAD). Understanding the genetic determinants of dyslipidemia can provide valuable information on the pathogenesis of CAD and aid in the development of early detection strategies. In this study, we used a Global Screening Array (GSA) to elucidate the genetic factors associated with dyslipidemia and their potential role in the prediction of CAD. We conducted a GSA-based association study in 265 subjects to identify the genetic loci associated with dyslipidemia traits using Multiple Linear Regression (MLR) and Logistic Regression (LR), Classification and Regression Tree (CART), and Manhattan plots. We identified an association between dyslipidemia and variants identified in genes such as JCAD, GLIS3, CD38, FN1, CELSR2, MTNR1B, GIPR, DYM, APOB, APOE, ADCY5. The MLR models explained 62%, 71%, and 81% of the variability in HDL, LDL, and triglycerides, respectively. The Area Under the Curve (AUC) values in the LR models of HDL, LDL, and triglycerides were 1.00, 0.94, and 0.95, respectively. CART models identified novel gene-gene interactions influencing the risk for dyslipidemia. To conclude, we have identified the association of 12 SNVs with dyslipidemia and demonstrated their clinical utility in four different models such as MLR, LR, CART, and Manhattan plots. The identified genetic variants and associated pathways shed light on the underlying biology of dyslipidemia and offer potential avenues for precision medicine strategies in the management of CAD.

The role of TLR7 agonists in modulating COVID-19 severity in subjects with loss-of-function TLR7 variants.

We investigate the mechanism associated with the severity of COVID-19 in men with TLR7 mutation. Men with loss-of-function (LOF) mutations in TLR7 had severe COVID-19. LOF mutations in TLR7 increased the risk of critical COVID by 16.00-fold (95% confidence interval 2.40-106.73). The deleterious mutations affect the binding of SARS-CoV2 RNA (- 328.66 ± 26.03 vs. - 354.08 ± 27.70, p = 0.03) and MYD88 (ß: 40.279, p = 0.003) to TLR7 resulting in the disruption of TLR7-MyD88-TIRAP complex. In certain hypofunctional variants and all neutral/benign variants, there is no disruption of TLR7-MyD88-TIRAP complex and four TLR7 agonists showed binding affinity comparable to that of wild protein. N-acetylcysteine (NAC) also showed a higher binding affinity for the LOF variants (p = 0.03). To conclude, TLR7 LOF mutations increase the risk of critical COVID-19 due to loss of viral RNA sensing ability and disrupted MyD88 signaling. Majority of hypofunctional and neutral variants of TLR7 are capable of carrying MyD88 signaling by binding to different TLR7 agonists and NAC.

Computational Fragment-Based Design of Phytochemical Derivatives as EGFR Inhibitors.

Epidermal growth factor receptor (EGFR) is a potential target with disease modifying benefits against Alzheimer's disease (AD). Repurposing of FDA approved drugs against EGFR have shown beneficial effect against AD but are confined to quinazoline, quinoline and aminopyrimidines. Futuristically, the possibility of acquiring drug resistance mutation as seen in the case of cancer could also hamper AD treatment. To identify novel chemical scaffolds, we rooted on phytochemicals identified from plants such as Acorus calamus, Bacopa monnieri, Convolvulus pluricaulis, Tinospora cordifloia, and Withania somnifera that have well-established records in the treatment of brain disorders. The rationale was to mimic the biosynthetic metabolite extension process observed in the plants for synthesizing new phytochemical derivates. Thus, novel compounds were designed computationally by fragment-based method followed by extensive in silico analysis to pick potential phytochemical derivates. PCD1, 8 and 10 were predicted to have better blood brain barrier permeability. ADMET and SoM analysis suggested that these PCDs exhibited druglike properties. Further simulation studies showed that PCD1 and PCD8 stably interact with EGFR and have the potential to be used even in cases of drug-resistance mutations. With further experimental evidence, these PCDs could be leveraged as potential inhibitors of EGFR.

Discovery of Novel Myristic Acid Derivatives as N-Myristoyltransferase Inhibitors: Design, Synthesis, Analysis, Computational Studies and Antifungal Activity.

In recent years, N-Myristoyltransferase (NMT) has been identified as a new target for the treatment of fungal infections. It is observed that at present, there are increased rates of morbidity and mortality due to fungal infections. Hence, a series of novel myristic acid derivatives were designed via molecular docking studies and ADMET studies by targeting NMT (N-Myristoyltransferase). The designed myristic acid derivatives were synthesized by converting myristic acid into myristoyl chloride and coupling it with aryl amines to yield corresponding myristic acid derivatives. The compounds were purified and characterized via FTIR, NMR and HRMS spectral analyses. In this study, we carried out a target NMT inhibition assay. In the NMT screening assay results, the compounds 3u, 3m and 3t showed better inhibition compared to the other myristic acid derivatives. In an in vitro antifungal evaluation, the myristic acid derivatives were assessed against Candida albicans and Aspergillus niger strains by determining their minimal inhibitory concentrations (MIC50). The compounds 3u, 3k, 3r and 3t displayed superior antifungal capabilities against Candida albicans, and the compounds 3u, 3m and 3r displayed superior antifungal capabilities against Aspergillus niger compared to the standard drug FLZ (fluconazole). Altogether, we identified a new series of antifungal agents.

Deciphering the emerging role of phytocompounds: Implications in the management of drug-resistant tuberculosis and ATDs-induced hepatic damage.

Tuberculosis is a disease of poverty, discrimination, and socioeconomic burden. Epidemiological studies suggest that the mortality and incidence of tuberculosis are unacceptably higher worldwide. Genomic mutations in embCAB, embR, katG, inhA, ahpC, rpoB, pncA, rrs, rpsL, gyrA, gyrB, and ethR contribute to drug resistance reducing the susceptibility of Mycobacterium tuberculosis to many antibiotics. Additionally, treating tuberculosis with antibiotics also poses a serious risk of hepatotoxicity in the patient's body. Emerging data on drug-induced liver injury showed that anti-tuberculosis drugs remarkably altered levels of hepatotoxicity biomarkers. The review is an attempt to explore the anti-mycobacterial potential of selected, commonly available, and well-known phytocompounds and extracts of medicinal plants against strains of Mycobacterium tuberculosis. Many studies have demonstrated that phytocompounds such as flavonoids, alkaloids, terpenoids, and phenolic compounds have antibacterial action against Mycobacterium species, inhibiting the bacteria's growth and replication, and sometimes, causing cell death. Phytocompounds act by disrupting bacterial cell walls and membranes, reducing enzyme activity, and interfering with essential metabolic processes. The combination of these processes reduces the overall survivability of the bacteria. Moreover, several phytochemicals have synergistic effects with antibiotics routinely used to treat TB, improving their efficacy and decreasing the risk of resistance development. Interestingly, phytocompounds have been presented to reduce isoniazid- and ethambutol-induced hepatotoxicity by reversing serum levels of AST, ALP, ALT, bilirubin, MDA, urea, creatinine, and albumin to their normal range, leading to attenuation of inflammation and hepatic necrosis. As a result, phytochemicals represent a promising field of research for the development of new TB medicines.

Dark fermentative hydrogen production: Potential of food waste as future energy needs.

Globally, food waste (FW) is found to be one of the major constituents creating several hurdles in waste management. On the other hand, the energy crisis is increasing and the limited fossil fuel resources available are not sufficient for energy needed for emerging population. In this context, biohydrogen production approach through valorization of FW is emerging as one of the sustainable and eco-friendly options. The present review explores FW sources, characteristics, and dark fermentative production of hydrogen along with its efficiency. FW are highly biodegradable and rich in carbohydrates which can be efficiently utilized by anaerobic bacteria. Based on the composition of FW, several pretreatment methods can be adapted to improve the bioavailability of the organics. By-products of dark fermentation are organic acids that can be integrated with several secondary bioprocesses. The versatility of secondary products is ranging from energy generation to biochemicals production. Integrated approaches facilitate in enhanced energy harvesting along with extended wastewater treatment. The review also discusses various parameters like pH, temperature, hydraulic retention time and nutrient supplementation to enhance the process efficiency of biohydrogen production. The application of solid-state fermentation (SSF) in dark fermentation improves the process efficiency. Dark fermentation as the key process for valorization and additional energy generating process can make FW the most suitable substrate for circular economy and waste based biorefinery.

Application of machine learning tools and integrated OMICS for screening and diagnosis of inborn errors of metabolism.

INTRODUCTION: Tandem mass spectrometry (TMS) has emerged an important screening tool for various metabolic disorders in newborns. However, there is inherent risk of false positive outcomes. Objective To establish analyte-specific cutoffs in TMS by integrating metabolomics and genomics data to avoid false positivity and false negativity and improve its clinical utility. METHODS: TMS was performed on 572 healthy and 3000 referred newborns. Urine organic acid analysis identified 23 types of inborn errors in 99 referred newborns. Whole exome sequencing was performed in 30 positive cases. The impact of physiological changes such as age, gender, and birthweight on various analytes was explored in healthy newborns. Machine learning tools were used to integrate demographic data with metabolomics and genomics data to establish disease-specific cut-offs; identify primary and secondary markers; build classification and regression trees (CART) for better differential diagnosis; for pathway modeling. RESULTS: This integration helped in differentiating B12 deficiency from methylmalonic acidemia (MMA) and propionic acidemia (Phi coefficient=0.93); differentiating transient tyrosinemia from tyrosinemia type 1 (Phi coefficient=1.00); getting clues about the possible molecular defect in MMA to initiate appropriate intervention (Phi coefficient=1.00); to link pathogenicity scores with metabolomics profile in tyrosinemia (r2=0.92). CART model helped in establishing differential diagnosis of urea cycle disorders (Phi coefficient=1.00). CONCLUSION: Calibrated cut-offs of different analytes in TMS and machine learning-based establishment of disease-specific thresholds of these markers through integrated OMICS have helped in improved differential diagnosis with significant reduction of the false positivity and false negativity rates.

Virtual Screening for Identification of Dual Inhibitors against CDK4/6 and Aromatase Enzyme.

CDK4/6 and aromatase are prominent targets for breast cancer drug discovery and are involved in abnormal cell proliferation and growth. Although aromatase inhibitors have proven to be effective (for example exemestane, anastrozole, letrozole), resistance to treatment eventually occurs through the activation of alternative signaling pathways, thus evading the antiproliferative effects of aromatase inhibitors. One of the evasion pathways is Cylin D-CDK4/6-Rb signaling that promotes tumor proliferation and resistance to aromatase inhibitors. There is significant evidence that the sequential inhibition of both proteins provides therapeutic benefits over the inhibition of one target. The basis of this study objective is the identification of molecules that are likely to inhibit both CDK4/6 and aromatase by computational chemistry techniques, which need further biochemical studies to confirm. Initially, a structure-based pharmacophore model was constructed for each target to screen the sc-PDB database. Consequently, pharmacophore screening and molecular docking were performed to evaluate the potential lead candidates that effectively mapped both of the target pharmacophore models. Considering abemaciclib (CDK4/6 inhibitor) and exemestane (aromatase inhibitor) as reference drugs, four potential virtual hit candidates (1, 2, 3, and 4) were selected based on their fit values and binding interaction after screening a sc-PDB database. Further, molecular dynamics simulation studies solidify the stability of the lead candidate complexes. In addition, ADMET and DFT calculations bolster the lead candidates. Hence, these combined computational approaches will provide a better therapeutic potential for developing CDK4/6-aromatase dual inhibitors for HR+ breast cancer therapy.

Novel Indole-Tethered Chromene Derivatives: Synthesis, Cytotoxic Properties, and Key Computational Insights.

Indole-tethered chromene derivatives were synthesised in a one-pot multicomponent reaction using N-alkyl-1H-indole-3-carbaldehydes, 5,5-dimethylcyclohexane-1,3-dione, and malononitrile, catalysed by DBU at 60-65 °C in a short reaction time. The benefits of the methodology include non-toxicity, an uncomplicated set-up procedure, a faster reaction time, and high yields. Moreover, the anticancer properties of the synthesised compounds were tested against selected cancer cell lines. The derivatives 4c and 4d displayed very good cytotoxic activity, with IC50 values ranging from 7.9 to 9.1 µM. Molecular docking revealed the potent derivatives have good binding affinity towards tubulin protein, better than the control, and the molecular dynamic simulations further demonstrated the stability of ligand-receptor interactions. Moreover, the derivatives followed all the drug-likeness filters.

Applications of Neural Network-Based Plan-Cancer Method for Primary Diagnosis of Mesothelioma Cancer.

"Malignant mesothelioma (MM)" is an uncommon although fatal form of cancer. The proper MM diagnosis is crucial for efficient therapy and has significant medicolegal implications. Asbestos is a carcinogenic material that poses a health risk to humans. One of the most severe types of cancer induced by asbestos is "malignant mesothelioma." Prolonged shortness of breath and continuous pain are the most typical symptoms of the condition. The importance of early treatment and diagnosis cannot be overstated. The combination "epithelial/mesenchymal appearance of MM," however, makes a definite diagnosis difficult. This study is aimed at developing a deep learning system for medical diagnosis MM automatically. Otherwise, the sickness might cause patients to succumb to death in a short amount of time. Various forms of artificial intelligence algorithms for successful "Malignant Mesothelioma illness" identification are explored in this research. In relation to the concept of traditional machine learning, the techniques support "Vector Machine, Neural Network, and Decision Tree" are chosen. SPSS has been used to analyze the result regarding the applications of Neural Network helps to diagnose MM.

Development of pharmacogenomic algorithm to optimize nateglinide dose for the treatment of type 2 diabetes mellitus.

BACKGROUND: Nateglinide is a meglitinide used for the treatment of type 2 diabetes mellitus. Individual studies demonstrated the association of CYP2C9, SLCO1B1, and MTNR1B variants with the safety and efficacy of nateglinide. The current study aimed to develop a pharmacogenomic algorithm to optimize nateglinide therapy. METHODS: Multiple linear regression (MLR) and classification and regression tree (CART) were used to develop a pharmacogenomic algorithm for nateglinide dosing based on the published nateglinide pharmacokinetic data on the area under the curve data (AUC) and Cmax (n = 143). CYP2C9 metabolizer phenotype, SLCO1B1, MTNR1B genotypes, and CYP2C9 inhibitor usage were used as the input variables. The results and associations were further confirmed by meta-analysis and in silico studies. RESULTS: The MLR models of AUC and Cmax explain 87.4% and 59% variability in nateglinide pharmacokinetics. The Bland and Altman analysis of the nateglinide dose predicted by these two MLR models showed a bias of ± 26.28 mg/meal. The CART algorithm was proposed based on these findings. This model is further justified by the meta-analysis showing increased AUCs in CYP2C9 intermediate metabolizers and SLCOB1 TC and CC genotypes compared to the wild genotypes. The increased AUC in SLCO1B1 mutants is due to decreased binding affinity of nateglinide to the mutant affecting the influx of nateglinide into hepatocytes. MTNR1B rs10830963 G-allele-mediated poor response to nateglinide is attributed to increased transcriptional factor binding causing decreased insulin secretion. CONCLUSION: CYP2C9, SLCO1B1, and MTNR1B genotyping help in optimizing nateglinide therapy based on this algorithm and ensuring safety and efficacy.

Molecular insights into the role of genetic determinants of congenital hypothyroidism.

In our previous studies, we have demonstrated the association of certain variants of the thyroid-stimulating hormone receptor (TSHR), thyroid peroxidase (TPO), and thyroglobulin (TG) genes with congenital hypothyroidism. Herein, we explored the mechanistic basis for this association using different in silico tools. The mRNA 3'-untranslated region (3'-UTR) plays key roles in gene expression at the post-transcriptional level. In TSHR variants (rs2268477, rs7144481, and rs17630128), the binding affinity of microRNAs (miRs) (hsa-miR-154-5p, hsa-miR-376a-2-5p, hsa-miR-3935, hsa-miR-4280, and hsa-miR-6858-3p) to the 3'-UTR is disrupted, affecting post-transcriptional gene regulation. TPO and TG are the two key proteins necessary for the biosynthesis of thyroid hormones in the presence of iodide and H2O2. Reduced stability of these proteins leads to aberrant biosynthesis of thyroid hormones. Compared to the wild-type TPO protein, the p.S398T variant was found to exhibit less stability and significant rearrangements of intra-atomic bonds affecting the stoichiometry and substrate binding (binding energies, ΔG of wild-type vs. mutant: ‒15 vs. ‒13.8 kcal/mol; and dissociation constant, Kd of wild-type vs. mutant: 7.2E-12 vs. 7.0E-11 M). The missense mutations p.G653D and p.R1999W on the TG protein showed altered ΔG (0.24 kcal/mol and 0.79 kcal/mol, respectively). In conclusion, an in silico analysis of TSHR genetic variants in the 3'-UTR showed that they alter the binding affinities of different miRs. The TPO protein structure and mutant protein complex (p.S398T) are less stable, with potentially deleterious effects. A structural and energy analysis showed that TG mutations (p.G653D and p.R1999W) reduce the stability of the TG protein and affect its structure-functional relationship.

Tissue-specific DNase I footprint analysis confirms the association of GATAD2B Q470* variant with intellectual disability.

Intellectual disability (ID) is a neurodevelopmental disorder in which genetics play a key aetiological role. GATA zinc finger domain-containing 2B (GATAD2B) gene encodes a zinc-finger protein transcriptional repressor which is a part of the methyl-CpG binding protein-1 complex. Pathogenic variants in this gene are linked to ID, dysmorphic features, and cognitive disability. To date, only 18 cases are reported worldwide and only one case is reported from India. A 12-year-old girl presented with a heterozygous nonsense variation in exon 8 of the GATAD2B gene (chr1:153785737G>A). She has severe ID and significant delayed developmental milestones along with clinical features including broad arched eyebrows, low-set ears, a bulbous nose tip, thin upper lip, and wide mouth with downturned corners. This is the second report of a heterozygous mutation in the GATAD2B gene from India with a novel phenotype. To substantiate the association of GATAD2B mutation with ID, we performed DNase I footprint analysis of wild and mutant DNA sequences to establish k-mer binding profile and deduced GATA binding affinity using human ENCODE experimental data of foetal brain. We observed that in the presence of variation, GATA zinc finger domain was altered thus contributing to ID. Our findings support the importance of the GATAD2B gene in the study of neurodevelopmental disorders.

Pharmacogenetic determinants of warfarin in the Indian population.

BACKGROUND: Several studies optimized the warfarin dose based on CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A, CYP4F2 V433M. But, the information on the rare variants is lacking. In this study, we have explored the prevalence of common and rare pharmacogenetic determinants of warfarin and determined their damaging nature. METHODS: We have analyzed 2000 healthy adults using the Infinium global screening array (GSA) for 15 pharmacogenetic determinants of warfarin. In addition, we have elucidated the impact of these variants on protein function, stability, dynamics, evolutionary preservation, and ligand binding propensity. RESULTS: The GSA Analysis has revealed that CYP4F2 V433M (MAF: 39.425%), VKORC1 -1639 G > A (MAF: 20.5%), CYP2C9*3 (MAF:9.925%), and CYP2C9*2 (MAF:4.575%) are common, while CYP2C9*14 (MAF: 1.475%), CYP2C9*4 (0.175%), CYP2C9*5 (0.125%), and CYP2C9*11 (0.125%) are rare. Position-specific evolutionary preservation (PSEP) analysis has revealed that CYP2C9*4 is possibly damaging, while CYP2C9*5, CYP2C9*11, and CYP2C9*14 are probably damaging. CYP2C9*4 has high thermolability (-10.14 kcal/mol). Among the rare CYP2C9 variants, CYP2C9*4 and CYP2C9*11 exert destabilizing effects and may have increased molecular flexibility, while CYP2C9*5 and CYP2C9*14 exert stabilizing effects and may have decreased molecular flexibility. DNase I footprint analysis has revealed the loss of the E-box consensus sequence due to VKORC1 -1639 G > A polymorphism. CONCLUSION: CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A and CYP4F2 V433M are common; CYP2C9*4, CYP2C9*5, CYP2C9*11, and CYP2C9*14 variants are rare in Indian subjects. All the CYP2C9 variants are found to be damaging. DNase I footprint analysis provided the mechanistic rationale for the association of VKORC1 -1639 G > A with warfarin sensitivity.

Utility of clinical exome sequencing in the evaluation of neonates with suspected genetic condition - An observational study from tertiary neonatal care unit in South India.

OBJECTIVES: To study the utility of clinical exome sequencing (CES) using next generation sequencing (NGS) in evaluating neonates with suspected genetic conditions. METHODS: This is an observational study conducted in a tertiary care neonatal unit. We included neonates with suspected genetic conditions, for whom CES were done either by direct sampling or from stored DNA. Data was collected from the Sri Ramachandra centre of excellence in perinatal health (SCOPE) case records of 2016-2019. Yield of CES, percentage of pathogenic, non-pathogenic and variant of uncertain significance (VUS) and associated disorders were studied. RESULTS: CES was done in 36 neonates. Variants were detected in 78% (28/36). However, significant variants with clinical correlation were present in 20 (56%) babies. Test was carried out from the stored sample in 10 (28%) babies. Mean turn-around time was 39 ± 7 days. Specialist was involved in 1 and treatment changes were done in 5 neonates. Five out of 8 VUS were clinically correlating. Inborn errors of metabolism were the commonest (60%). Two VUS were ascertained as likely pathogenic after parental segregation analysis. CONCLUSION: CES has a definite role in evaluation of suspected genetic conditions for diagnosis and prognostication. It also helps scientific society to build in additional evidence so that the "VUS" could be asserted as "likely pathogenic" . Our experience reiterates the importance of storing and archiving DNA of the affected child.

Alpha synuclein (SNCA) rs7684318 variant contributes to Parkinson's disease risk by altering transcription factor binding related with Notch and Wnt signaling.

In view of inconsistencies in the association studies of alpha synuclein (SNCA) rs7684318 (chr4: 90655003 T > C) with Parkinson's disease (PD), we conducted a meta-analysis to establish the association of this variant with PD and examined changes in transcription factor binding. SNCA rs7684318 C-allele was identified as genetic risk factor for PD in fixed (OR: 1.53, 95 % CI: 1.40-1.68, p < 0.0001) and random effect (OR: 1.65, 95 % CI: 1.30-2.09, p = 0.0003) models. Heterogeneity was observed in association (Tau2: 0.0576, H: 2.32, I2: 0.815, Q: 21.64, p = 0.0002). Egger's test showed no evidence of publication bias (p = 0.37). Subgroup analysis showed that rs7684318 is contributing to PD risk in Japanese (OR: 1.46, 95 % CI: 1.30-1.64) and Indian (OR: 2.63, 95 % CI: 1.79-3.86) populations while showing no significant association in Chinese population (OR: 1.68, 95 % CI: 0.93-3.02). Sensitivity analysis showed that exclusion of any one of the studies has no significant impact on the association, which justifies the robustness of the analysis. Tissue-specific DNase foot print analysis revealed that this variant contributes to increased transcription factor binding in midbrain, putamen and caudate nucleus. The substitution of T > C increased binding of RBPJ and GATA-family transcription factors; and decreased binding of NKX2 family, SNAI2, SNAI3, DMRT1, HOXA13, HOXB13, HOXC13, HOXD13, WT1, POU4F1, POU4F2, POU4F3 transcriptional factors. TRANSFAC and DNA curvature analyses substantiate the association of this variant with increased binding of GATA1 that contribute to intensity of DNA curvature peaks and splitting pattern. These studies along with the meta-analysis strongly suggest that the rs7684318 variant contributes to the pathophysiology of PD by modulating binding of transcription factors related to Notch and Wnt signalling pathways that are likely to impair dopmanergic transmission.

Influence of RFC1 c.80A>G Polymorphism on Methotrexate-Mediated Toxicity and Therapeutic Efficacy in Rheumatoid Arthritis: A Meta-analysis.

BACKGROUND: Methotrexate (MTX) is an antirheumatic drug, transported by reduced folate carrier-1 (RFC1). The most common RFC1 gene variant, c.80 A>G (rs1051266) is ambiguously linked to adverse effects of MTX therapy in some rheumatoid arthritis (RA) patients. OBJECTIVE: The purpose of meta-analysis was to summarize all major published studies on c.80 A>G SNP to clarify this ambiguity in MTX therapy. METHODS: A total of 18 studies representing 3592 RA patients comprising 699 men and 2893 women were included. Both fixed and random effect models were applied to study the data. RESULTS: The RFC1 80A-allele showed null association with MTX-mediated toxicity in both fixed (odds ratio [OR] = 0.91; 95% CI = 0.80-1.03) and random effects (OR = 0.89; 95% CI: 0.71-1.11) models. Because heterogeneity was observed in this association (P = 0.0006), data were segregated based on use of folate therapy. In 7 studies (n = 1191) where folate was used along with MTX, RFC1 AA patients showed reduced risk for MTX-mediated toxicity (OR = 0.67; 95% CI: 0.50-0.89; P = 0.0006). The RFC1 80A-allele was found to increase the efficacy of MTX therapy by 1.53-fold (95% CI: 1.24-1.88), whereas the 80AA-genotype increased the efficacy by 1.85-fold (95% CI: 1.41-2.42). No publication bias was observed in these associations. CONCLUSION AND RELEVANCE: RFC1 c.80 A>G is an important pharmacogenetic determinant of MTX therapy in RA. The RFC1 80A-allele robustly increased therapeutic efficacy and safety when folate was used along with MTX. Findings are relevant to decision-making in the clinical use of MTX as a treatment for RA patients harboring the RFC1 gene variant.