Genome-wide association (GWA) studies apply broad DNA scans on hundreds-of-thousands of common sequence variants in thousands of people for the purpose of mapping trait- or disease-related loci. We provide examples of ligand- and target-based studies from the field of age-related macular degeneration (AMD) to demonstrate the value of the GWA approach in confirmatory and exploratory pharmacogenomics research. Complementing this genomic analysis, we used a simple biochemical retinal pigment epithelium (RPE) oxidative, apoptotic high throughput screening (HTS) assay to identify compounds. This ligand-to-targetto DNA sequence variant-to disease approach provided guidance on rational design of preclinical studies and identified associations between: 1) valproic acid and advanced AMD-associated genes with the capacity to alter GABA-succinate signaling (ALDH5A1, CACNA1C, SUCLA2, and GABBR2) and chromatin remodeling (HDAC9); and 2) Ropinirole and a geographic atrophy-associated gene (DRD3) with the capacity to alter systems involved in cAMP-PKA signaling. In both applications of our method, the breadth of GWA findings allowed efficient expansion of results to identify enriched pathways and additional ligands capable of targeting pathway constituents. A disease associated SNP-to gene-to target-to ligand approach provided guidance to inform preventive and therapeutic preclinical studies investigating roles of targets in: 1) PPAR-RXR transcription complex constituents for neovascular AMD; and 2) the stress activated MAPK signaling cascade constituents for advanced AMD. Our conclusion is that publically available data from GWA studies can be used successfully with open-access genomics, proteomics, structural chemistry, and pharmacogenomics databases in an efficient, rational approach to streamline the processes of planning and implementation for confirmatory and exploratory pre-clinical studies of preventive or therapeutic pharmacologic treatments for complex diseases.

Background: Alopecia areata (AA) is a type of alopecia or hair loss, which is very common in human. It is classified as an autoimmune disorder, which has a variable course. It can be either relapsing or persistent type. The persistent type is seen in patients with extensive hair loss. AA affects young people most commonly with an age less than 20 years but can also concern adults. It makes up to 4% dermatology cases in China, around 2-3% in UK and USA and 0.7% in India. Patients with alopecia have social and economic suffering due to anxiety symptoms, avoidance behavior, and social anxiety disorder, making it a very important non lethal disease to study. Methods: In the present study, microarray datasets GDS5274 and GDS5272 of AA have been re-analyzed from mouse as well as human respectively. The simultaneous analysis of model organism and patient data has provided two pronged validation approach to delineate potential biomarkers of the disease. Out of 45101 genes of model organism (Mus musculus), and 54675 genes of patient (Homo sapiens), top 100 up regulated and down regulated genes were selected and further analyzed by DAVID and Enrichr tools for KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, GO (gene ontology) (cellular component, molecular function and biological process). Results: Four genes viz. CXCL9, CXCL10, STAT1 and CCL5 were differentially regulated in both organisms, hence can be considered as plausibly contributing in triggering the AA. The network and pathway analysis by PathwayLinker2.0 revealed the partners of these crucial genes i.e. CCR1, CCR5, IGFBP7, VCAN, DPP4, CCR3, CXCR3 through which these genes might coordinate to manifest hair fall.Conclusions: The dual analysis approach has helped to generate plausible novel biomarkers of the disease for diagnostic and therapeutic approach. Stimulation of any of these biomarkers by various triggers can damage hair follicle. These genes can be targeted therapeutically to halt the hair follicle damage by inhibiting their expression hence, providing novel future drug targets for AA.

The authors have withdrawn this preprint due to author disagreement.