Epistasis Blog

From the Computational Genetics Laboratory at Dartmouth Medical School (www.epistasis.org)

Saturday, February 11, 2012

Six Degrees of Epistasis

This is a nice overview of network methods for addressing gene-gene interactions. Our recent paper on the topic came out too late to be included. See Hu et al. (2011).

McKinney BA, Pajewski NM. Six Degrees of Epistasis: Statistical Network Models for GWAS. Front Genet. 2011;2:109. [PubMed]

Abstract

There is growing evidence that much more of the genome than previously thought is required to explain the heritability of complex phenotypes. Recent studies have demonstrated that numerous common variants from across the genome explain portions of genetic variability, spawning various avenues of research directed at explaining the remaining heritability. This polygenic structure is also the motivation for the growing application of pathway and gene set enrichment techniques, which have yielded promising results. These findings suggest that the coordination of genes in pathways that are known to occur at the gene regulatory level also can be detected at the population level. Although genes in these networks interact in complex ways, most population studies have focused on the additive contribution of common variants and the potential of rare variants to explain additional variation. In this brief review, we discuss the potential to explain additional genetic variation through the agglomeration of multiple gene-gene interactions as well as main effects of common variants in terms of a network paradigm. Just as is the case for single-locus contributions, we expect each gene-gene interaction edge in the network to have a small effect, but these effects may be reinforced through hubs and other connectivity structures in the network. We discuss some of the opportunities and challenges of network methods for analyzing genome-wide association studies (GWAS) such as the study of hubs and motifs, and integrating other types of variation and environmental interactions. Such network approaches may unveil hidden variation in GWAS, improve understanding of mechanisms of disease, and possibly fit into a network paradigm of evolutionary genetics.

Tuesday, February 07, 2012

Genetic Epidemiology with a Capital E

Great new article by Duncan Thomas that raises a number of very interesting questions about genome-wide association studies (GWAS), Big Science, dominant journals with large influence and the role of consortia in the sociology of sciences. Worth a read.

Here is an excerpt:

"Another feature of GWAS having become routine is the emergence of consortia for discovering smaller and smaller risks because of the need for enormous sample sizes [Hunter et al., 2007]. This pressure towards Big Science will doubtless become even stronger as we move into sequence data and look for rarer variants. There are some issues in the sociology of science that are worth attention:

How are new investigators to find their niche in such an environment without becoming lost in a list of hundreds of authors?

What is the role of investigator-initiated studies and novel or paradigm-shifting ideas?

Is the dominance of a single journal, by virtue of its impact factor, in setting the agenda for the entire field a good thing?

Is the huge burden of time and effort required to establish these consortia really worth the yield of smaller and smaller effect sizes?

Certainly these consortia can be expected to yield more and more—and finer and finer—gold dust, but what about the nuggets?

How are we to deal with the requirement of replication when a consortium has essentially the corner on all the available data or in unique situations (e.g., a gene-environment interaction with an unusual or unusually well-characterized exposure)—perhaps by some form of internal cross-validation?"

Duncan C. Thomas. Genetic Epidemiology with a Capital E: Where Will We Be in Another 10 Years? Genetic Epidemiology, in press (2012) [Wiley]

Abstract:

In a commentary on the evolution of the field of genetic epidemiology over the past 10 years, Khoury et al. (2011) highlight several important developments, including the emergence of evaluation of genetic discoveries for their translational utility and of standards for reporting genetic findings. In this companion to their article, I reflect on some of these trends and speculate about the direction of the field in the future. In particular, I emphasize the opportunities posed by novel technologies like next-generation sequencing and the biological insights emerging from integrative genomics, but I also question the utility of large consortia. The basic principles of population-based research and the importance of taking account of the environment remain important to the field.