Transcriptome analysis of AMD retina reveals convergent molecular pathology

Abstract

Purpose : AMD has seen spectacular success in deciphering the genetic underpinnings with 52 common and rare variants at 34 loci identified to date. Yet, the mechanism through which associated variants confer liability has not been extensively explored. Post-GWAS, variation in gene expression regulation has been established as a major basis of complex disease risk. However, a comprehensive analysis of gene expression and regulation in healthy and diseased retina has been lacking in the field. Here we describe transcriptome analysis (RNAseq) and whole genome genotyping of human retinae of over 500 donor retinas at different stages of AMD to address some of these challenges.

Methods : Donor eyes were evaluated for absence/presence and severity of AMD using the Minnesota Grading Systems. Retina samples from 128 controls, 197 early AMD, 126 intermediate AMD and 66 advanced AMD of were analyzed. RNA and DNA was isolated using TRIzol^®, libraries were made with the TruSeq^® Stranded mRNA Library Preparation Kit and sequencing was performed on the Illumina Hiseq 2500. Reads were aligned to the Ensembl 38.5 using STAR, and RSEM was used to estimate gene- and transcript level quantification. Differential analysis was performed using limma; DAVID and GO was used for pathways analysis. WGCNA was employed to identify discrete gene modules based on co-expressions between genes. Genotyping was generated on a custom-modified HumanCoreExome array, followed by imputation using Haplotype Reference Consortium (HRC) panel on Michigan Imputation Server.

Results : Pathway analysis of differentially expressed genes revealed stage-specific progression of AMD from healthy tissue to advanced stages. Several AMD associated genes, especially those associated with immune response, were up regulated in early stages with later alterations in complement and extracellular matrix pathways. WGCNA analysis identified several co-expression modules in normal and AMD retina. We are currently performing eQTL analysis for evaluating the impact of risk variants on gene regulation to gain novel insights into AMD.

Conclusions : Our data represent the largest resource of gene expression and its genetic regulation in vision research. Our findings highlight the genes, pathways and regulatory mechanisms involved in AMD. Additionally, it provides a useful resource for functional dissection of multiple other vision related traits.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.