VIRdb: a comprehensive database for interactive analysis of genes/proteins involved in the pathogenesis of vitiligo.

Vitiligo is a chronic asymptomatic disorder affecting melanocytes from the basal layer of the epidermis which leads to a patchy loss of skin color. Even though it is one of the neglected disease conditions, people suffering from vitiligo are more prone to psychological disorders. As of now, various studies have been done in order to project auto-immune implications as the root cause. To understand the complexity of vitiligo, we propose the Vitiligo Information Resource (VIRdb) that integrates both the drug-target and systems approach to produce a comprehensive repository entirely devoted to vitiligo, along with curated information at both protein level and gene level along with potential therapeutics leads. These 25,041 natural compounds are curated from Natural Product Activity and Species Source Database. VIRdb is an attempt to accelerate the drug discovery process and laboratory trials for vitiligo through the computationally derived potential drugs. It is an exhaustive resource consisting of 129 differentially expressed genes, which are validated through gene ontology and pathway enrichment analysis. We also report 22 genes through enrichment analysis which are involved in the regulation of epithelial cell differentiation. At the protein level, 40 curated protein target molecules along with their natural hits that are derived through virtual screening. We also demonstrate the utility of the VIRdb by exploring the Protein-Protein Interaction Network and Gene-Gene Interaction Network of the target proteins and differentially expressed genes. For maintaining the quality and standard of the data in the VIRdb, the gold standard in bioinformatics toolkits like Cytoscape, Schrödinger's GLIDE, along with the server installation of MATLAB, are used for generating results. VIRdb can be accessed through "http://www.vitiligoinfores.com/".

VIRdb 2.0: Interactive analysis of comorbidity conditions associated with vitiligo pathogenesis using co-expression network-based approach.

Vitiligo is a disease of mysterious origins in the context of its occurrence and pathogenesis. The autoinflammatory theory is perhaps the most widely accepted theory that discusses the occurrence of Vitiligo. The theory elaborates the clinical association of vitiligo with autoimmune disorders such as Psoriasis, Multiple Sclerosis and Rheumatoid Arthritis and Diabetes. In the present work, we discuss the comprehensive set of differentially co-expressed genes involved in the crosstalk events between Vitiligo and associated autoimmune disorders (Psoriasis, Multiple Sclerosis and Rheumatoid Arthritis). We progress our previous tool, Vitiligo Information Resource (VIRdb), and incorporate into it a compendium of Vitiligo-related multi-omics datasets and present it as VIRdb 2.0. It is available as a web-resource consisting of statistically sound and manually curated information. VIRdb 2.0 is an integrative database as its datasets are connected to KEGG, STRING, GeneCards, SwissProt, NPASS. Through the present study, we communicate the major updates and expansions in the VIRdb and deliver the new version as VIRdb 2.0. VIRdb 2.0 offers the maximum user interactivity along with ease of navigation. We envision that VIRdb 2.0 will be pertinent for the researchers and clinicians engaged in drug development for vitiligo.

Effect of noninsulin antidiabetic drugs added to metformin therapy on glycemic control, weight gain, and hypoglycemia in type 2 diabetes.

CONTEXT: Metformin is the recommended initial drug therapy for patients with type 2 diabetes mellitus (DM). However, the optimal second-line drug when metformin monotherapy fails is unclear. OBJECTIVE: To determine the comparative efficacy, risk of weight gain, and hypoglycemia associated with noninsulin antidiabetic drugs in patients with type 2 DM not controlled by metformin alone. DATA SOURCES: A literature search via MEDLINE (beginning in January 1950) and Cochrane CENTRAL through January 2010 and a manual search of references for additional relevant studies. STUDY SELECTION: Randomized controlled trials (RCTs) with at least 3 months' duration, evaluating noninsulin antidiabetic drugs added to metformin in patients experiencing an inadequate response to maximized and stable (> or = 4 weeks at > or = 1500 mg or maximally tolerated dose) metformin therapy. DATA EXTRACTION: Inclusion/exclusion criteria; duration of patient follow-up; drug, dose, and schedule used; use of concurrent lifestyle modification; and baseline characteristics (age, sex, anthropometrics, glycated hemoglobin A(1c) [HbA(1c)], duration of DM, and metformin dose). End points collected included mean change in HbA(1c), proportion of patients achieving HbA(1c) goal of less than 7%, change in weight, and incidence of hypoglycemia. Mixed-treatment comparison meta-analysis was used to calculate the weighted mean difference for changes from baseline in HbA(1c) and body weight and relative risk (RR) of HbA(1c) goal attainment and hypoglycemia, with associated 95% credible intervals. DATA SYNTHESIS: Overall, 27 RCTs (n = 11 198) were included. Mean (range) trial duration was 32 (12-52) weeks. The different classes of drugs were associated with similar HbA(1c) reductions (range, 0.64%-0.97%) compared with placebo. Although use of thiazolidinediones, sulfonylureas, and glinides were associated with weight gain (range, 1.77-2.08 kg), glucagon-like peptide-1 analogs, alpha-glucosidase inhibitors, and dipeptidyl peptidase-4 inhibitors were associated with weight loss or no weight change. Sulfonylureas and glinides were associated with higher rates of hypoglycemia than with placebo (RR range, 4.57-7.50). CONCLUSION: When added to maximal metformin therapy, all noninsulin antidiabetic drugs were associated with similar HbA(1c) reductions but differed in their associations with weight gain and risk of hypoglycemia.