Three splendid papers on type 2 diabetes in Science yesterday set a new standard for genome wide associations (GWAS) and emphasize the importance of multiple replications. For those with strong nerves, competitive collaboration is a fine way in which to scrutinize the evidence for robust associations.
Several new loci have been successfully identified. In addition, these papers are now the best available model for the ideal way to publish GWAS results showing the genetic landscape of common diseases once the most prominent associations have been noted. Below, I list some of the highlights of the Science papers from the point of view of an editor looking forward to robust standards of proof in this new field.
David Altshuler in Nicholas Wade’s article in the NYTimes April 26th
“I tip my hat to DeCode,” he said. "But the technology is now widely available,” and in his view the only barrier to other teams contributing to gene discovery would be if they dropped the high standards of statistical rigor developed by the three academic consortiums.
10.1126/science.1142364 Zeggini et al.
“The first wave of validated SNPs sent for replication was selected from the 30 SNPs, in 9 distinct chromosomal regions (excluding TCF7L2) which had, in the WTCCC scan alone, attained the most extreme (P<10-5) significance values on Cochran-Armitage tests of association.”
MA: I hope the Wellcome Trust Case-Control Consortium scan (unpublished, but cited by Zeggini et al. as a personal communication from Peter Donnelly and the WTCCC) does not provide a precedent for using a single trend test to establish association in a single step!
10.1126/science.1142364 Zeggini et al.
“We prioritized the 5367 SNPs in this range, using additional criteria: (a): evidence of association in DGI and FUSION (6,7); b) presence of multiple, independent (r2 < 0.4) associations within the same locus; and © biological candidacy (8, 18).“
MA: (a) yes, (b) good idea, let’s add that criterion, © no, this seems like moving the dogs back to the lamp post, to abuse Francis Collins’s metaphor :
Lauran Neergaard, ”https://www.wtopnews.com/?nid=106&sid=1126266">AP April 26th
“We have been for all of the last decade or more looking under the lamppost to try to find those genes … and lots of times the lamplight was not actually where we wanted it,” said Dr. Francis Collins, genetics chief at the National Institutes of Health, a co-author of the research unveiled Thursday. This new approach “allows us to light up the whole street, and look what we find.”
10.1126/science.1142364 Zeggini et al.
“Our study provides an important validation of the genome-wide indirect association mapping approach and a demonstration of the value of aggressive data sharing efforts."
MA: giggles
10.1126/science.1142382 Scott et al.
“….we….imputed genotypes for an additional >2 million autosomal SNPs.”
MA: This is the shape of the future. Both Goncalo Abecasis and Peter Donnelly have talked recently at conferences about getting lots more science for the genotyping by using the HapMap to impute genotypes.
10.1126/science/ 1142358 DGI Broad/ Lund/Novartis
“Given this distribution, and as WGAS are hypothesis generating, we sought replication in independent samples.”
MA: Amen, brother.
10.1126/science/ 1142358 DGI Broad/ Lund/Novartis
….“An intriguing aspect of this association in its location far from any annotated gene.”
MA: Yes, this phenomenon was found for prostate cancer too. I think it may be common for common disease associations: enhancers etc. can be far from the nearest gene and we must expect other mechanisms at work not consistently affecting transcription in a haplotype-specific manner.
10.1126/science/ 1142358 DGI Broad/ Lund/Novartis
“We observe strong evidence (P<10-4, rank in the top 100) for six previously reported common variants that influence lipid levels (Table 3).”
MA: Admittedly this is post-hoc and the previously reported variants were chosen by similar methods, but this replication seems enormously reassuring.