Integrated Multi-Omics Analysis and Validation in Yeast Model of Amyotrophic Lateral Sclerosis.

Transcriptomics is a complex process that involves raw data extraction, normalization, differential gene expression, and analysis. The Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (NCBI) is a repository of experimental datasets. Amyotrophic lateral sclerosis (ALS) datasets are deposited by various scientists and research investigators to expand the horizon of scientific knowledge. R-statistical tools are the most common ways for conducting these kinds of studies. The first step is the identification of appropriate datasets. Since the raw data is available in a variety of formats, a large array of software is used for extraction and analysis. Normalization is conducted for the datasets using NetworkAnalyst. Differential analysis is further conducted on the normalized data to identify significantly enriched genes. The significant genes are then grouped into pathways. The results were validated using yeast model of ALS in which the yeast is transformed with ALS plasmids encoding genes associated with ALS. The resulting GFP-tagged protein aggregates are imaged using fluorescence microscopy and subsequently validated using filter retardation assay and quantified using ImageJ software. Functional role of different genes is studied using metabolite treatment and knockout studies.

Adenosine deaminase modulates metabolic remodeling and orchestrates joint destruction in rheumatoid arthritis.

Rheumatoid Arthritis (RA) is a chronic autoimmune disease associated with inflammation and joint remodeling. Adenosine deaminase (ADA), a risk factor in RA, degrades adenosine, an anti-inflammatory molecule, resulting in an inflammatory bias. We present an integrative analysis of clinical data, cytokines, serum metabolomics in RA patients and mechanistic studies on ADA-mediated effects on in vitro cell culture models. ADA activity differentiated patients into low and high ADA sets. The levels of the cytokines TNFα, IFNγ, IL-10, TGFß and sRANKL were elevated in RA and more pronounced in high ADA sets. Serum metabolomic analysis shows altered metabolic pathways in RA which were distinct between low and high ADA sets. Comparative analysis with previous studies shows similar pathways are modulated by DMARDs and biologics. Random forest analysis distinguished RA from control by methyl-histidine and hydroxyisocaproic acid, while hexose-phosphate and fructose-6-phosphate distinguished high ADA from low ADA. The deregulated metabolic pathways of High ADA datasets significantly overlapped with high ADA expressing PBMCs GEO transcriptomics dataset. ADA induced the death of chondrocytes, synoviocyte proliferation, both inflammation in macrophages and their differentiation into osteoclasts and impaired differentiation of mesenchymal stem cells to osteoblasts and mineralization. PBMCs expressing elevated ADA had increased expression of cytokines and P2 receptors compared to synovial macrophages which has low expression of ADA. Our data demonstrates increased cytokine levels and distinct metabolic signatures of RA based on the ADA activity, suggests an important role for ADA in the pathophysiology of RA joints and as a potential marker and therapeutic target in RA patients.

Elevated dimethylarginine, ATP, cytokines, metabolic remodeling involving tryptophan metabolism and potential microglial inflammation characterize primary open angle glaucoma.

Glaucoma of which primary open angle glaucoma (POAG) constitutes 75%, is the second leading cause of blindness. Elevated intra ocular pressure and Nitric oxide synthase (NOS) dysfunction are hallmarks of POAG. We analyzed clinical data, cytokine profile, ATP level, metabolomics and GEO datasets to identify features unique to POAG. N9 microglial cells are used to gain mechanistic insights. Our POAG cohort showed elevated ATP in aqueous humor and cytokines in plasma. Metabolomic analysis showed changes in 21 metabolites including Dimethylarginine (DMAG) and activation of tryptophan metabolism in POAG. Analysis of GEO data sets and previously published proteomic data sets bins genes into signaling and metabolic pathways. Pathways from reanalyzed metabolomic data from literature significantly overlapped with those from our POAG data. DMAG modulated purinergic signaling, ATP secretion and cytokine expression were inhibited by N-Ethylmaleimide, NO donors, BAPTA and purinergic receptor inhibitors. ATP induced elevated intracellular calcium level and cytokines expression were inhibited by BAPTA. Metabolomics of cell culture supernatant from ATP treated sets showed metabolic deregulation and activation of tryptophan metabolism. DMAG and ATP induced IDO1/2 and TDO2 were inhibited by N-Ethylmaleimide, sodium nitroprusside and BAPTA. Our data obtained from clinical samples and cell culture studies reveal a strong association of elevated DMAG, ATP, cytokines and activation of tryptophan metabolism with POAG. DMAG mediated ATP signaling, inflammation and metabolic remodeling in microglia might have implications in management of POAG.

Systems analysis of avascular necrosis of femoral head using integrative data analysis and literature mining delineates pathways associated with disease.

Avascular necrosis of femoral head (AVNFH) is a debilitating disease, which affects the middle aged population. Though the disease is managed using bisphosphonate, it eventually leads to total hip replacement due to collapse of femoral head. Studies regarding the association of single nucleotide polymorphisms with AVNFH, transcriptomics, proteomics, metabolomics, biophysical, ultrastructural and histopathology have been carried out. Functional validation of SNPs was carried out using literature. An integrated systems analysis using the available datasets might help to gain further insights into the disease process. We have carried out an analysis of transcriptomic data from GEO-database, SNPs associated with AVNFH, proteomic and metabolomic data collected from literature. Based on deficiency of vitamins in AVNFH, an enzyme-cofactor network was generated. The datasets are analyzed using ClueGO and the genes are binned into pathways. Metabolomic datasets are analyzed using MetaboAnalyst. Centrality analysis using CytoNCA on the data sets showed cystathionine beta synthase and methylmalonyl-CoA-mutase to be common to 3 out of 4 datasets. Further, the genes common to at least two data sets were analyzed using DisGeNET, which showed their involvement with various diseases, most of which were risk factors associated with AVNFH. Our analysis shows elevated homocysteine, hypoxia, coagulation, Osteoclast differentiation and endochondral ossification as the major pathways associated with disease which correlated with histopathology, IHC, MRI, Micro-Raman spectroscopy etc. The analysis shows AVNFH to be a multi-systemic disease and provides molecular signatures that are characteristic to the disease process.