Elevated ATP, cytokines and potential microglial inflammation distinguish exfoliation glaucoma from exfoliation syndrome

Consolidating data on the association of IL-6 and IL-10 polymorphisms with the development of glaucoma: a meta-analysis

BACKGROUND

The study aimed to investigate the association of IL-6 and IL-10 polymorphisms with susceptibility to glaucoma by analyzing all relevant individual studies.

MATERIALS AND METHODS

Relevant articles were gathered from PubMed, Web of Science, Embase, WanFang, and CNKI databases up to 15 October 2023. Odds ratios (ORs) were used to evaluate the association strengths, along with 95% confidence intervals (CIs).

RESULTS

Seven case-control studies involving 1408 cases and 1789 controls on the IL-6 -174 G>C polymorphism, and three studies with 675 cases and 1100 controls on the IL-6 -572 G>C were included. Moreover, three separate studies, each comprising 442 cases and 672 controls, investigated the IL-10 -592C>A, -819T>C, and -1082A>G polymorphisms. The combined data indicated a significant association between -592C>A, -819T>C, and -1082A>G at IL-10 gene and IL-6 -572 G>C with glaucoma susceptibility, with no correlation found for IL-6 -174 G>C.

CONCLUSIONS

The study found that IL-10 -592C>A, -819T>C, -1082A>G, and IL-6 -572 G>C polymorphisms were linked to glaucoma risk. However, no significant association was observed for IL-6 -174 G>C. These findings imply a possible connection between genetic variations in these genes and glaucoma risk. Further research is crucial to fully understand the underlying mechanisms and their significance in managing and preventing glaucoma.

Tecoma stans Floral Extract-Based Biosynthesis for Enhanced Surface Plasmon-Coupled Emission and a Preliminary Study on Fluoroimmunoassay

We demonstrate the synthesis of biogenic supported silver spiked star architectures and their application to increase the electromagnetic field intensity at its tips that enhance plasmon-coupled emission. Tecoma stans floral extract has been used to synthesize silver nanocubes and spiked stars. We observe ∼445-fold and ∼680-fold enhancements in spacer and cavity configurations, respectively, in the SPCE platform. The hotspot intensity and Purcell factor are evaluated by carrying out finite-difference time-domain (FDTD) simulations. Time-based studies are presented to modulate the sharpness of the edges wherein an increase in the tip sharpness with the increase in reaction time up to 5 h is observed. The unique morphology of the silver architectures allowed us to utilize them in biosensing application. A SPCE-based fluoroimmunoassay was performed, achieving a 1.9 pg/mL limit of detection of TNF-α cytokine. This combination of anisotropic architectures, SPCE and immunoassay prove to be a powerful platform for the ultrasensitive detection of biomarkers in surface-bound assays.

Metabolic deregulation associated with aging modulates protein aggregation in the yeast model of Huntington's disease

Huntington's disease is associated with increased CAG repeat resulting in an expanded polyglutamine tract in the protein Huntingtin (HTT) leading to its aggregation resulting in neurodegeneration. Previous studies have shown that N-terminal HTT with 46Q aggregated in the stationary phase but not the logarithmic phase in the yeast model of HD. We carried out a metabolomic analysis of logarithmic and stationary phase yeast model of HD expressing different polyQ lengths attached to N-terminal HTT tagged with enhanced green fluorescent protein (EGFP). The results show significant changes in the metabolic profile and deregulated pathways in stationary phase cells compared to logarithmic phase cells. Comparison of metabolic pathways obtained from logarithmic phase 46Q versus 25Q with those obtained for presymptomatic HD patients from our previous study and drosophila model of HD showed considerable overlap. The arginine biosynthesis pathway emerged as one of the key pathways that is common in stationary phase yeast compared to logarithmic phase and HD patients. Treatment of yeast with arginine led to a significant decrease, while transfer to arginine drop-out media led to a significant increase in the size of protein aggregates in both logarithmic and stationary phase yeast model of HD. Knockout of arginine transporters in the endoplasmic reticulum and vacuole led to a significant decrease in mutant HTT aggregation. Overall our results highlight arginine as a critical metabolite that modulates the aggregation of mutant HTT and disease progression in HD.Communicated by Ramaswamy H. Sarma.

Integrated clinical and metabolomic analysis of dengue infection shows molecular signatures associated with host-pathogen interaction in different phases of the disease

PURPOSE

Dengue is a mosquito vector-borne disease caused by the dengue virus, which affects 125 million people globally. The disease causes considerable morbidity. The disease, based on symptoms, is classified into three characteristic phases, which can further lead to complications in the second phase. Molecular signatures that are associated with the three phases have not been well characterized. We performed an integrated clinical and metabolomic analysis of our patient cohort and compared it with omics data from the literature to identify signatures unique to the different phases.

METHODS

The dengue patients are recruited by clinicians after standard-of-care diagnostic tests and evaluation of symptoms. Blood from the patients was collected. NS1 antigen, IgM, IgG antibodies, and cytokines in serum were analyzed using ELISA. Targeted metabolomics was performed using LC-MS triple quad. The results were compared with analyzed transcriptomic data from the GEO database and metabolomic data sets from the literature.

RESULTS

The dengue patients displayed characteristic features of the disease, including elevated NS1 levels. TNF-α was found to be elevated in all three phases compared to healthy controls. The metabolic pathways were found to be deregulated compared to healthy controls only in phases I and II of dengue patients. The pathways represent viral replication and host response mediated pathways. The major pathways include nucleotide metabolism of various amino acids and fatty acids, biotin, etc. CONCLUSION: The results show elevated TNF-α and metabolites that are characteristic of viral infection and host response. IL10 and IFN-γ were not significant, consistent with the absence of any complications.

Integrated multi-omics analysis of Alzheimer's disease shows molecular signatures associated with disease progression and potential therapeutic targets

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the formation of amyloid plaques implicated in neuronal death. Genetics, age, and sex are the risk factors attributed to AD. Though omics studies have helped to identify pathways associated with AD, an integrated systems analysis with the available data could help to understand mechanisms, potential biomarkers, and therapeutic targets. Analysis of transcriptomic data sets from the GEO database, and proteomic and metabolomic data sets from literature was performed to identify deregulated pathways and commonality analysis identified overlapping pathways among the data sets. The deregulated pathways included those of neurotransmitter synapses, oxidative stress, inflammation, vitamins, complement, and coagulation pathways. Cell type analysis of GEO data sets showed microglia, endothelial, myeloid, and lymphoid cells are affected. Microglia are associated with inflammation and pruning of synapses with implications for memory and cognition. Analysis of the protein-cofactor network of B2, B6, and pantothenate shows metabolic pathways modulated by these vitamins which overlap with the deregulated pathways from the multi-omics analysis. Overall, the integrated analysis identified the molecular signature associated with AD. Treatment with anti-oxidants, B2, B6, and pantothenate in genetically susceptible individuals in the pre-symptomatic stage might help in better management of the disease.

Systems biology approach delineates critical pathways associated with disease progression in rheumatoid arthritis

Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease leading to inflammation, cartilage cell death, synoviocyte proliferation, and increased and impaired differentiation of osteoclasts and osteoblasts leading to joint erosions and deformities. Transcriptomics, proteomics, and metabolomics datasets were analyzed to identify the critical pathways that drive the RA pathophysiology. Single nucleotide polymorphisms (SNPs) associated with RA were analyzed for the functional implications, clinical outcomes, and blood parameters later validated by literature. SNPs associated with RA were grouped into pathways that drive the immune response and cytokine production. Further gene set enrichment analysis (GSEA) was performed on gene expression omnibus (GEO) data sets of peripheral blood mononuclear cells (PBMCs), synovial macrophages, and synovial biopsies from RA patients showed enrichment of Th1, Th2, Th17 differentiation, viral and bacterial infections, metabolic signalling and immunological pathways with potential implications for RA. The proteomics data analysis presented pathways with genes involved in immunological signaling and metabolic pathways, including vitamin B12 and folate metabolism. Metabolomics datasets analysis showed significant pathways like amino-acyl tRNA biosynthesis, metabolism of amino acids (arginine, alanine aspartate, glutamate, glutamine, phenylalanine, and tryptophan), and nucleotide metabolism. Furthermore, our commonality analysis of multi-omics datasets identified common pathways with potential implications for joint remodeling in RA. Disease-modifying anti-rheumatic drugs (DMARDs) and biologics treatments were found to modulate many of the pathways that were deregulated in RA. Overall, our analysis identified molecular signatures associated with the observed symptoms, joint erosions, potential biomarkers, and therapeutic targets in RA. Communicated by Ramaswamy H. Sarma.