Aims: To assess the genetic correlation between refractive error in (a) European vs. East Asian adults, (b) European children vs. European adults, and (c) European children vs. East Asian adults.

Hypothesis: The above genetic correlations are high (i.e. greater than 0.5), which implies that the higher prevalence of myopia in East Asians compared to Europeans is not simply genetic in origin.

Variables: Refractive error will be based on autorefractor measurement. Within each of the 3 subject cohorts, refractive error will be rank-transformed to a give a Normal Score, using Blom's method. (Our ultimate aim is to compare the refractive error of individuals of different ethnicity/age after accounting for absolute differences due to the environment in which they grew up. Also, heritability analysis is not robust against departures from normal trait distributions).

Analysis method: The degree of genetic relatedness between all pairs of individuals in 2 cohorts combined will be calculated using the GCTA program (for the 3 sets of 2 cohorts listed as a, b and c in the Aims above). Bivariate variance components analysis will be carried out using GCTA, as described [4].

Preliminary work: We have used bivariate GCTA in ALSPAC YPs to show that the shared SNP-heritability across childhood is high (greater than 0.7) (unpublished results). Too few ALSPAC mothers have refractive error information for estimation of its SNP-heritability (unpublished results).

Precautions to ensure the identity of participants cannot be revealed: Under certain circumstances, access to high-density genotype data is sufficient to reveal the identity (e.g. surname) of an individual [5]. We propose the following scheme to make such identification impossible (given current knowledge):

a) Create a list of the SNPs present on the genotyping platform used for each of the 3 cohorts (ALSPAC, Rotterdam, Nagahama).

b) Identify SNPs genotyped in all 3 cohorts. Sort the list by chromosome, then by genomic position.

c) From the list generated in step (b) randomly delete 5% of SNPs.

d) From the list generated in step (c) randomly re-order the SNPs within chromosomes (i.e. shuffle the order of SNPs on chromosome 1, then shuffle the order of SNPs on chromosome 2, etc.).

e). Send the list generated in step (d) to each site (ALSPAC, Rotterdam, Nagahama).

f) At each site, an analyst links refractive error and genotype data. The order of subjects in the data file is then randomised, and the unique subject identifier (e.g. "ALN") is replaced with a new identifier based on file order, e.g. ALSPAC1, ALSPAC2, ALSPAC3, ... ALSPAC9999.

g) For the data file generated in step (f), the analyst at each site sorts the order of SNPs so that it matches the order of SNPs in the circulated list (e). SNPs missing from the list are deleted.

g) For the data file generated in step (g), the analyst at each site replaces the SNP name with a new name based on chromosome and file order, e.g. chr1snp1, chr1snp2, chr1,snp3, ...chr22snp3455.

h) The analyst at each site sends the file generated in step (g) to a central site for GCTA analysis.

NB. Without knowing the order of SNPs in the circulated list (e), the order of SNPs in the data files (h) is unknown, and thus cannot be used to infer identity....yet it can be used to calculate relatedness of subjects whose SNPs are sorted in the same order.

References

1. Pan CW, Ramamurthy D, Saw SM (2012) Worldwide prevalence and risk factors for myopia. Ophthalmic and Physiological Optics 32: 3-16.

2. Morgan IG, Ohno-Matsui K, Saw SM (2012) Myopia. Lancet 379: 1739-1748.

3. Verhoeven VJM, Hysi PG, Wojciechowski R, Fan Q, Guggenheim JA, et al. (2013) Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia. Nature Genetics 45: 314-318.

4. de Candia Teresa R, Lee SH, Yang J, Browning Brian L, Gejman Pablo V, et al. (2013) Additive genetic variation in schizophrenia risk is shared by populations of African and European descent. American Journal of Human Genetics 93: 463-470.

5. Gymrek M, McGuire AL, Golan D, Halperin E, Erlich Y (2013) Identifying personal genomes by surname inference. Science 339: 321-324.