Defining the causal relationship between epigenetic patterns and phenotype.

<p>Analysis of the respective relationships between DNA methylation (CpG), body mass index (BMI), and cardiovascular disease (CVD) can help to inform the direction of causality. An observed association between BMI and CpG and CpG and CVD will not decipher which of the depicted scenarios apply.</p

Incorporating epigenetic information in a Mendelian randomization framework.

<p>(A) Alcohol exposure is associated with risk of head and neck squamous cell carcinoma (HNSCC) and this may be mediated by altered DNA methylation (CpG). The relationship between alcohol exposure and HNSCC is potentially confounded by factors such as socio-economic position, which correlate with both exposure and disease. A common variant in ADH1B can be used as an unconfounded, genetic proxy for alcohol exposure, and if this SNP is associated with CpG (either locally or more widely across the genome), it would lend support to the hypothesis that alcohol intake causally influences DNA methylation. However, showing associations of these epigenetic measures with HNSCC does not demonstrate causality of either alcohol or CpG on HNSCC, as either or both associations (alcohol→HNSCC and CpG→HNSCC) could be confounded or alcohol could influence HNSCC through another pathway (dashed line). (B) To investigate this, another Mendelian randomization experiment could be undertaken using an SNP known to have a <i>cis</i> influence on loci-specific DNA methylation. If an association were observed between this SNP and both CpG and HNSCC, this would support a role for DNA methylation in the causation of HNSCC.</p

Applying Mendelian randomization to define the causal relationship between phenotype and disease.

<p>An example based upon the report of Lintel-Nietschke et al. (2008) <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1000356#pmed.1000356-LinselNitschke1" target="_blank">[74]</a> reporting the association between a gene variant in the <i>LDLR</i> gene with decreased low density lipoprotein-cholesterol (LDL-C) levels and with a reduced risk of coronary artery disease (CAD). The variant can be used in a Mendelian randomization approach to test the causal relationship between LDL-C and CAD. If LDL-C has a causal role in CAD, an association between the <i>LDLR</i> gene variant and disease risk would be seen (red dashed arrow). If LDL-C levels are correlated with CAD risk but not causal, then the gene variant will not show an association with CAD risk. This will establish whether reverse causation is at play and remove the potential confounding influence of factors such as smoking and nutritional status.</p

Epigenetic modifications.

<p>Chromosomes are composed of chromatin, consisting of DNA wrapped around eight histone protein units. Each DNA-bound histone octamer is a nucleosome. Histone tails protruding from histone proteins are decorated with modifications, including phosphorylation (Ph), methylation (Me), and acetylation (Ac). DNA molecules are methylated by the addition of a methyl group to carbon position 5 on cytosine bases when positioned adjacent to a guanine base (CpG sites), a reaction catalyzed by DNA methyltransferase enzymes. DNA methylation maintains repressed gene activity. Transcription involves the conversion of DNA to messenger RNA (mRNA), which is usually repressed by DNA methylation and histone deacetylation. mRNA is translated into a protein product, but this process can be repressed by binding of microRNA (miRNA) to mRNA. Each miRNA binds to the mRNA of up to 200 gene targets. miRNAs can also be involved in establishing DNA methylation and may influence chromatin structure by regulating histone modifiers.</p

Male odds ratios for wheeze in the last 12 months and asthma in the last 12 months, in ALSPAC.

<p>Male odds ratios for wheeze in the last 12 months and asthma in the last 12 months, in ALSPAC.</p

Characteristics of wheeze and asthma outcomes in the MCS by sex, with follow-up rates at each time-point as a percentage of total cohort size for each sex (total MCS = 8850 males and 8458 females).

<p>Characteristics of wheeze and asthma outcomes in the MCS by sex, with follow-up rates at each time-point as a percentage of total cohort size for each sex (total MCS = 8850 males and 8458 females).</p

Male odds ratios for ever wheeze, ever asthma and wheeze in the last 12 months in the MCS at 4 time-points.

<p>Male odds ratios for ever wheeze, ever asthma and wheeze in the last 12 months in the MCS at 4 time-points.</p

Estimated prevalence of wheezing at each time-point from 3.1 to 10.7 years for each of the four wheezing phenotypes identified by latent class analysis in 7349 participants with complete observations of wheeze in the last 12 months in the MCS.

<p>Estimated prevalence of wheezing at each time-point from 3.1 to 10.7 years for each of the four wheezing phenotypes identified by latent class analysis in 7349 participants with complete observations of wheeze in the last 12 months in the MCS.</p

Concepts of (A) confounding and (B) mediation in epidemiological studies illustrated using a Directed acyclic graph (DAG).

<p>In the case of sex and asthma, where sex is the exposure and asthma status the outcome, any extraneous factors must go by the mediation pathway, as nothing can influence a child’s sex at conception.</p

Longitudinal logistic models using cubic splines of repeated wheeze and asthma measures by sex.

<p>Males are in blue and females in red. Shaded areas represent 95% confidence intervals. Measures of (A) asthma in the last 12 months in ALSPAC (B) wheeze in the last 12 months in ALSPAC (C) asthma ever in the MCS (D) wheeze in the last 12 months in the MCS and (E) wheeze ever in the MCS.</p