Genome-Wide Association Study of Retinal Layer Thickness

GWAS were implemented using an additive linear model in BGENIE [18 (link)]. The mean thickness of each component PRC layer across the ETDRS grid was used as the input phenotype (Fig 1C). Eye-specific covariates including image quality measures obtained from the OCT machine (listed above) and refractive error (calculated as sphericalerror + 0.5 × cylindricalerror) were regressed out of thickness values for the left and right eye separately before a mean was made across the two eyes. Covariates including age, weight, sex, height, OCT machine ID and the first 20 genotype PCs were used in the model. A genome-wide significance threshold of P <5 × 10^-8 was used. LD-score regression was implemented using LD SCore v1.0 [20 (link)] to obtain estimates of genomic inflation and heritability of traits.

Free full text: Click here

Currant H., Fitzgerald T.W., Patel P.J., Khawaja A.P., Webster A.R., Mahroo O.A, & Birney E. (2023). Sub-cellular level resolution of common genetic variation in the photoreceptor layer identifies continuum between rare disease and common variation. PLOS Genetics, 19(2), e1010587.

Publication 2023

Eyes Genomic Genotype Gwas Phenotype Refractive error

Corresponding Organization : St Thomas' Hospital

Other organizations : Novo Nordisk Foundation, University of Copenhagen

Top 5 similar protocols

Variable analysis

independent variables

Genotype data

dependent variables

Mean thickness of each component PRC layer across the ETDRS grid

control variables

Weight
Height
OCT machine ID
The first 20 genotype PCs
Eye-specific covariates including image quality measures obtained from the OCT machine and refractive error (calculated as spherical error + 0.5 × cylindrical error)

positive controls

None specified

negative controls

None specified

Annotations

Based on most similar protocols

Etiam vel ipsum. Morbi facilisis vestibulum nisl. Praesent cursus laoreet felis. Integer adipiscing pretium orci. Nulla facilisi. Quisque posuere bibendum purus. Nulla quam mauris, cursus eget, convallis ac, molestie non, enim. Aliquam congue. Quisque sagittis nonummy sapien. Proin molestie sem vitae urna. Maecenas lorem.

As authors may omit details in methods from publication, our AI will look for missing critical information across the 5 most similar protocols.

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Revolutionizing how scientists
search and build protocols!