Meta-analysis investigating the impact of the LEPR rs1137101 (A>G) polymorphism on obesity risk in Asian and Caucasian ethnicities.

Obesity is a chronic condition which is identified by the buildup of excess body fat caused by a combination of various factors, including genetic predisposition and lifestyle choices. rs1137101 (A > G) polymorphism in the CHR1 domain of LEPR protein linked to different diseases including obesity. Nevertheless, the connection between this polymorphism and the likelihood of developing obesity has not been determined definitively. Therefore, a meta-analysis was conducted to assess the relationship between rs1137101 and the risk of obesity. The meta-analysis included all studies meeting pre-defined criteria, found through searching databases up until February 2023. A combined odds ratio with a 95% confidence interval was estimated as overall and in continent subgroups for homozygous, heterozygous, recessive, dominant and allelic models using the fixed or the random-effects model. The meta-analysis identified 39 eligible studies with cases and controls (6099 cases/6711 controls) in 38 articles under different ethnic backgrounds. The results indicated a significant relationship between rs1137101 and the likelihood of developing obesity in each of the genetic models [the homozygous model (GG vs. AA: 95% Confidence Interval = 1.12-1.73, Odds Ratio = 1.39, P value = 0.003); the heterozygous model (AG vs. AA: 95% Confidence Interval = 1.07-1.42, Odds Ratio = 1.23, P value = 0.005); the dominant model (AG/GG vs AA: 95% Confidence Interval = 1.10-1.49, Odds Ratio = 1.28, P value = 0.001); the recessive model (GG vs AA/AG: 95% Confidence Interval = 1.02-1.45, Odds Ratio = 1.21, P value = 0.03); and the allelic model (G vs A; 95% Confidence Interval = 1.07-1.33, Odds Ratio = 1.19, P value = 0.002)] tested. Additionally, with an FDR <0.05, all genotypic models demonstrated statistical significance. The association remained significant among subgroups of Asian and Caucasian populations, although analysis in some genetic models did not show a significant association. Begg's and Egger's tests did not show publication biases. In sensitivity analysis, one particular study was found to have an impact on the Recessive model's significance, but other models remained unaffected. The current meta-analysis found significant indications supporting the association between rs1137101 and obesity. To avail a deeper understanding of this association, future research should include large-scale studies conducted in diverse ethnic populations.

Synthetic augmentation of bilirubin metabolism in human pluripotent stem cell-derived liver organoids.

UGT1A1 (UDP glucuronosyltransferase family 1 member A1) is the primary enzyme required for bilirubin conjugation, which is essential for preventing hyperbilirubinemia. Animal models lack key human organic anion transporting polypeptides with distinct epigenetic control over bilirubin metabolism, necessitating a human model to interrogate the regulatory mechanism behind UGT1A1 function. Here, we use induced pluripotent stem cells to develop human liver organoids that can emulate conjugation failure phenotype. Bilirubin conjugation assays, chromatin immunoprecipitation, and transcriptome analysis elucidated the role of glucocorticoid antagonism in UGT1A1 activation. This antagonism prevents the binding of transcriptional repressor MECP2 at the expense of NRF2 with associated off-target effects. Therefore, we introduced functional GULO (L-gulonolactone oxidase) in human organoids to augment intracellular ascorbate for NRF2 reactivation. This engineered organoid conjugated more bilirubin and protected against hyperbilirubinemia when transplanted in immunosuppressed Crigler-Najjar syndrome rat model. Collectively, we demonstrate that our organoid system serves as a manipulatable model for interrogating hyperbilirubinemia and potential therapeutic development.

Identification of novel inhibitors of high affinity iron permease (FTR1) through implementing pharmacokinetics index to fight against black fungus: An in silico approach.

Mucormycosis is a life-threatening fungal infection, particularly in immunocompromised patients. Mucormycosis has been reported to show resistance to available antifungal drugs and was recently found in COVID-19 as a co-morbidity that demands new classes of drugs. In an attempt to find novel inhibitors against the high-affinity iron permease (FTR1), a novel target having fundamental importance on the pathogenesis of mucormycosis, 11,000 natural compounds were investigated in this study. Virtual screening and molecular docking identified two potent natural compounds [6',7,7,10',10',13'-hexamethylspiro[1,8-dihydropyrano[2,3-g]indole-3,11'-3,13-diazatetracyclo[5.5.2.01,9.03,7]tetradecane]-2,9,14'-trione and 5,7-dihydroxy-3-(2,2,8,8-tetramethylpyrano[2,3-f]chromen-6-yl)chromen-4-one] that effectively bind to the active cavity of FTR1 with a binding affinity of -9.9 kcal/mol. Multiple non-covalent interactions between the compounds and the active residues of this cavity were noticed, which is required for FTR1 inhibition. These compounds were found to have inhibitory nature and meet essential requirements to be drug-like compounds with a considerable absorption, distribution, metabolism, and excretion (ADME) profile with no toxicity probabilities. Molecular dynamics simulation confirms the structural compactness and less conformational variation of the drug-protein complexes maintaining structural stability and rigidity. MM-PBSA and post-simulation analysis predict binding stability of these compounds in the active cavity. This study hypothesizing that these compounds could be a potential inhibitor of FTR1 and will broaden the clinical prospects of mucormycosis.

Computational epigenetic landscape analysis reveals association of CACNA1G-AS1, F11-AS1, NNT-AS1, and MSC-AS1 lncRNAs in prostate cancer progression through aberrant methylation.

Aberrant expression of long non-coding RNAs (lncRNAs), caused by alterations in DNA methylation, is a driving factor in several cancers. Interplay between lncRNAs' aberrant methylation and expression in prostate cancer (PC) progression still remains largely elusive. Therefore, this study characterized the genome-wide epigenetic landscape and expression profiles of lncRNAs and their clinical impact by integrating multi-omics data implementing bioinformatics approaches. We identified 62 differentially methylated CpG-sites (DMCs) and 199 differentially expressed lncRNAs (DElncRNAs), where 32 DElncRNAs contain 32 corresponding DMCs within promoter regions. Significant negative correlation was observed between 8 DElncRNAs-DMCs pairs. 3 (cg23614229, cg23957912, and cg11052780) DMCs and 4 (CACNA1G-AS1, F11-AS1, NNT-AS1, and MSC-AS1) DElncRNAs were identified as high-risk factors for poor prognosis of PC patients. Overexpression of hypo-methylated CACNA1G-AS1, F11-AS1, and NNT-AS1 and down-regulation of hyper-methylated MSC-AS1 significantly lower the survival of PC patients and could be a potential prognostic and therapeutic biomarker. These DElncRNAs were found to be associated with several molecular functions whose deregulation can lead to cancer. Involvement of these epigenetically deregulated DElncRNAs in cancer-related biological processes was also noticed. These findings provide new insights into the understanding of lncRNA regulation by aberrant DNA methylation which will help to clarify the epigenetic mechanisms underlying PC.

Genome-wide identification and prediction of SARS-CoV-2 mutations show an abundance of variants: Integrated study of bioinformatics and deep neural learning.

Genomic data analysis is a fundamental system for monitoring pathogen evolution and the outbreak of infectious diseases. Based on bioinformatics and deep learning, this study was designed to identify the genomic variability of SARS-CoV-2 worldwide and predict the impending mutation rate. Analysis of 259044 SARS-CoV-2 isolates identified 3334545 mutations with an average of 14.01 mutations per isolate. Globally, single nucleotide polymorphism (SNP) is the most prevalent mutational event. The prevalence of C > T (52.67%) was noticed as a major alteration across the world followed by the G > T (14.59%) and A > G (11.13%). Strains from India showed the highest number of mutations (48) followed by Scotland, USA, Netherlands, Norway, and France having up to 36 mutations. D416G, F106F, P314L, UTR:C241T, L93L, A222V, A199A, V30L, and A220V mutations were found as the most frequent mutations. D1118H, S194L, R262H, M809L, P314L, A8D, S220G, A890D, G1433C, T1456I, R233C, F263S, L111K, A54T, A74V, L183A, A316T, V212F, L46C, V48G, Q57H, W131R, G172V, Q185H, and Y206S missense mutations were found to largely decrease the structural stability of the corresponding proteins. Conversely, D3L, L5F, and S97I were found to largely increase the structural stability of the corresponding proteins. Multi-nucleotide mutations GGG > AAC, CC > TT, TG > CA, and AT > TA have come up in our analysis which are in the top 20 mutational cohort. Future mutation rate analysis predicts a 17%, 7%, and 3% increment of C > T, A > G, and A > T, respectively in the future. Conversely, 7%, 7%, and 6% decrement is estimated for T > C, G > A, and G > T mutations, respectively. T > G\A, C > G\A, and A > T\C are not anticipated in the future. Since SARS-CoV-2 is mutating continuously, our findings will facilitate the tracking of mutations and help to map the progression of the COVID-19 intensity worldwide.

Organoid transplant approaches for the liver.

Organoid technology is a state-of-the-art cell culture tool that has revolutionized study of development, regeneration, and diseases. Human liver organoids (HLOs) are now derived from either adult stem/progenitors or pluripotent stem cells (PSCs), emulating cellular diversity and structural symphony akin to the human liver. With the rapid rise in decompensated liver disease conditions only treated by liver transplant therapy, HLOs represent an alternate source for transplantation to address the ongoing shortage of grafts. Although ongoing advancements in bioengineering technology have moved the organoid transplant approach to the next level, sustained survival of the transplanted tissue still eludes us toward functional organ replacement. Herein, we review the development of HLOs and discuss promises and challenges on organoid transplant approaches.

A cohort study on the association of MDM2 SNP309 with lung cancer risk in Bangladeshi population.

BACKGROUND/AIMS: Bangladesh is a densely populated country with an increased incidence of lung cancer, mostly due to smoking. Therefore, elucidating the association of mouse double minute 2 homolog (MDM2) single nucleotide polymorphism (SNP) 309 (rs2279744) with lung cancer risk from smoking in Bangladeshi population has become necessary. METHODS: DNA was extracted from blood samples of 126 lung cancer patient and 133 healthy controls. The MDM2 SNP309 was genotyped by polymerase chain reaction- restriction fragment length polymorphism (PCR-RFLP), using the restriction enzymes MspA1I. Logistic regression was then carried out to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to estimate the risk of lung cancer. A meta-analysis of SNP309 was also carried out on 12,758 control subjects and 11,638 patient subjects. RESULTS: In multivariate logistic regression, significantly increased risk of lung cancer was observed for MDM2 SNP309 in the dominant model (TG + GG vs. TT: OR, 2.13; 95% CI, 1.29 to 3.53). Stratification analysis revealed that age, sex, obesity, and smoking also increases the risk of lung cancer when carrying the MDM2 SNP309. Our meta-analysis revealed that MDM2 SNP309 was considerably associated with lung cancer in Asian populations (TG + GG vs. TT: OR, 1.32; 95% CI , 1.12 to 1.56; p = 0.019 for heterogeneity). CONCLUSION: The MDM2 SNP309 was associated with high risk of lung cancer in Bangladeshi and Asian population, particularly with increased age, smoking, and body mass index.