Epistasis Blog

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

Tuesday, July 29, 2014

Innovation is often unnerving: the door into summer

My latest BioData Mining editorial with Dr. James Malley from NIH. We discuss innovation and interestingness within the context of biological data mining.

Malley JD, Moore JH. Innovation is often unnerving: the door into summer. BioData Min. 2014 Jul 17;7:12. [PDF]

Monday, June 09, 2014

Validated context-dependent associations of coronary heart disease risk with genotype variation

An absolutely fabulous paper from Charlie Sing and Andy Clark on the context-dependent effects of GWAS hits. A must read for anyone that believes, as I do, that the assumption of simplicity of genetic architecture is not realistic for most biological traits in humans. I have included below a paper for the PRIM method they used. Also worth a read.

Lusk CM, Dyson G, Clark AG, Ballantyne CM, Frikke-Schmidt R, Tybjærg-Hansen A, Boerwinkle E, Sing CF. Validated context-dependent associations of coronary heart disease risk with genotype variation in the chromosome 9p21 region: the Atherosclerosis Risk in Communities study. Hum Genet. 2014 Jun 3. [PubMed]

Dyson G, Sing CF. Efficient identification of context dependent subgroups of risk from genome-wide association studies. Stat Appl Genet Mol Biol. 2014 Apr 1;13(2):217-26. [PubMed]

Dyson G, Frikke-Schmidt R, Nordestgaard BG, Tybjaerg-Hansen A, Sing CF. Modifications to the Patient Rule-Induction Method that utilize non-additive combinations of genetic and environmental effects to define partitions that predict ischemic heart disease. Genet Epidemiol. 2009 May;33(4):317-24. [PubMed]

Friday, May 02, 2014

Models in Biology

This is by far one of the best papers I have read in the past year. Very relevant to our efforts to build mathematical, statistical and computation models of the genotype-phenotype relationship in population-based studies of common diseases. Gunawardena BMC Biology 2014, 12:29 [PDF]                  

Sunday, April 27, 2014

Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility

We have previously published a statistical epistasis network associated with bladder cancer in a population based study (Hu et al., BMC Bioinformatics). This network was highly non-random and contained many genes that were part of the aryl hydrocarbon receptor pathway. Below is a short paper reporting functional genomics annotation of the network.

Hu T, Pan Q, Andrew AS, Langer JM, Cole MD, Tomlinson CR, Karagas MR, Moore JH. Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility. BioData Min. 2014 Apr 11;7(1):5. [BioData Mining]


BACKGROUND: Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility.

FINDINGS: To support our statistical findings using networks, in the present study, we performed pathway enrichment analyses on the set of genes identified using SEN, and found that they are associated with the carcinogen benzo[a]pyrene, a component of tobacco smoke. We further carried out an mRNA expression microarray experiment to validate statistical genetic interactions, and to determine if the set of genes identified in the SEN were differentially expressed in a normal bladder cell line and a bladder cancer cell line in the presence or absence of benzo[a]pyrene. Significant nonrandom sets of genes from the SEN were found to be differentially expressed in response to benzo[a]pyrene in both the normal bladder cells and the bladder cancer cells. In addition, the patterns of gene expression were significantly different between these two cell types.

CONCLUSIONS: The enrichment analyses and the gene expression microarray results support the idea that SEN analysis of bladder in population-based studies is able to identify biologically meaningful statistical patterns. These results bring us a step closer to a systems genetic approach to understanding cancer susceptibility that integrates population and laboratory-based studies.

Monday, April 14, 2014

To replicate or not to replicate? The case of pharmacogenetic studies

Statistical replication has always been the gold standard in genome-wide association studies (GWAS). However, as we have previously pointed out, there are many good reasons why true genetic associations might not replicate (Greene et al. 2009). This 2013 paper explores the issue with respect to pharmacogenetic studies. The mantra of GWAS is now focused on the identification of new drug targets using genetic association results. If this is true, should biological validation matter more than statistical replication? 

Aslibekyan S, Claas SA, Arnett DK. To replicate or not to replicate: the case of pharmacogenetic studies: Establishing validity of pharmacogenomic findings: from replication to triangulation. Circ Cardiovasc Genet. 2013 Aug;6(4):409-12 [PubMed]

Sunday, April 13, 2014

Why human disease-associated residues appear as the wild-type in other species: genome-scale structural evidence for the compensation hypothesis

Xu J, Zhang J. Why human disease-associated residues appear as the wild-type in other species: genome-scale structural evidence for the compensation hypothesis. Mol Biol Evol. 2014 [PubMed]


Many human-disease associated amino acid residues (DARs) appear as the wild-type in other species. This phenomenon is commonly explained by the presence of compensatory residues in these other species that alleviate the deleterious effects of the DARs. The general validity of this hypothesis, however, is unclear, because few compensatory residues have been identified. Here we test the compensation hypothesis by assembling and analyzing 1077 DARs located in 177 proteins of known crystal structures. Because destabilizing protein structures is a primary reason why DARs are deleterious, we focus on protein stability in this analysis. We discover that, in species where a DAR represents the wild-type, the destabilizing effect of the DAR is generally lessened by the observed amino acid substitutions in the spatial proximity of the DAR. This and other findings provide genome-scale evidence for the compensation hypothesis and have important implications for understanding epistasis in protein evolution and for using animal models of human diseases.

Saturday, April 12, 2014

Detection and replication of epistasis influencing transcription in humans

This study demonstrates that replicable epistasis is common at the level of transcription.

Hemani G, Shakhbazov K, Westra HJ, Esko T, Henders AK, McRae AF, Yang J, Gibson G, Martin NG, Metspalu A, Franke L, Montgomery GW, Visscher PM, Powell JE. Detection and replication of epistasis influencing transcription in humans. Nature. 2014 Apr 10;508(7495):249-53. [PubMed]


Epistasis is the phenomenon whereby one polymorphism's effect on a trait depends on other polymorphisms present in the genome. The extent to which epistasis influences complex traits and contributes to their variation is a fundamental question in evolution and human genetics. Although often demonstrated in artificial gene manipulation studies in model organisms, and some examples have been reported in other species, few examples exist for epistasis among natural polymorphisms in human traits. Its absence from empirical findings may simply be due to low incidence in the genetic control of complex traits, but an alternative view is that it has previously been too technically challenging to detect owing to statistical and computational issues. Here we show, using advanced computation and a gene expression study design, that many instances of epistasis are found between common single nucleotide polymorphisms (SNPs). In a cohort of 846 individuals with 7,339 gene expression levels measured in peripheral blood, we found 501 significant pairwise interactions between common SNPs influencing the expression of 238 genes (P = 2.91 × 10(-16)). Replication of these interactions in two independent data sets showed both concordance of direction of epistatic effects (P = 5.56 × 10(-31)) and enrichment of interaction P values, with 30 being significant at a conservative threshold of P < 9.98 × 10(-5). Forty-four of the genetic interactions are located within 5 megabases of regions of known physical chromosome interactions (P = 1.8 × 10(-10)). Epistatic networks of three SNPs or more influence the expression levels of 129 genes, whereby one cis-acting SNP is modulated by several trans-acting SNPs. For example, MBNL1 is influenced by an additive effect at rs13069559, which itself is masked by trans-SNPs on 14 different chromosomes, with nearly identical genotype-phenotype maps for each cis-trans interaction. This study presents the first evidence, to our knowledge, for many instances of segregating common polymorphisms interacting to influence human traits.

Friday, February 14, 2014

Promotion and tenure review at universities

There is an interesting thread on promotion and tenure by @phylogenomics on twitter using the hashtag #publishperish14. He is tweeting comments from @lindakateh, the chancellor at UC Davis. All the tweets from the conference have been archived here. Some of the discussion was related to whether everyone should have tenure since very few actually don't get it. I also like the comments about the tenure process reducing creativity and risk-taking. She also discussed the idea of rewarding faculty for other forms of expression including blogs.

Wednesday, February 12, 2014

P-values, the 'gold standard' of statistical validity, are not as reliable as many scientists assume

This piece in Nature about the limitations of p-values is a must read. It is very relevant to genetics, epidemiology and, especially, genome-wide association studies (GWAS) that have put so much emphasis on p-values. We have also written about the limitations of p-values in a short editorial.

Thursday, January 30, 2014

Reconciling clinical importance and statistical significance in GWAS

Genome-wide association studies (GWAS) have identified many risk-associated SNPs with very small effects. The mantra for identifying more associations is to greatly increase the sample size to be able to detect smaller and smaller effects. This wonderful letter in the European Journal of Human Genetics points out that at some point the effect size goes below the measurement error calling into question the clinical significance of these GWAS hits. If I were funding a big GWAS study I would first want to know whether increasing the sample size is justified given the effects sizes to be detected and the error of the phenotype measures.

Shriner D, Adeyemo A, Rotimi CN. Reconciling clinical importance and statistical significance. Eur J Hum Genet. 2014 Feb;22(2):158-9. [EJHG]