There has been limited success in identifying causal variants underlying association signals observed in genome-wide association studies (GWAS). The use of 1000 Genomes Project (1KGP) allows the imputation to estimate the genetic information at untyped variants. However, long stretches of high linkage disequilibrium within the genome prevent us from differentiating between causal variants and perfect surrogates, thus limiting our ability to identify causal variants. Transethnic strategies have been proposed as a possible solution to mitigate this. However, these studies generally rely on imputing genotypes from multiple ancestries from 1KGP but not against population-specific reference panels. Here, we perform the first transethnic fine-mapping study across three Asian cohorts from diverse ancestries at the loci implicated with eye and blood lipid traits, using population-specific reference panels that have been generated by whole-genome sequencing samples from the same ancestry groups. Our study outlines several challenges faced in a fine-mapping exercise where one simply aims to meta-analyse existing GWAS that have been imputed against reference haplotypes from the 1KGP.