Most associated linear combinations of phenotypes at genome-wide significant SNPs.

*<p>indicates that the SNP did not have a univariate genome-wide significant <i>P</i> value. Each row indicates the linear combination of phenotypes (given by the corresponding regression coefficients) which is most associated with the given SNP under the MultiPhen regression, after removing the most associated phenotype. The regression coefficients have been scaled so that the CHOL coefficient is always equal to one. The last row contains the expected coefficients according to the Friedewald Formula (Equation 1).</p

Genome-wide significant results from standard GWAS approach and MultiPhen tested on combinations of the lipids using NFBC1966 data.

<p>Each bar shows the number of SNPs reaching genome-wide significance for a given phenotype-combination analysis (specified by the first letters of each trait, such that CHL refers to an analysis on the CHOL, HDL and LDL), with the SNPs discovered by both the univariate approach and MultiPhen shown by the white segment of the bar, the SNPs discovered by the univariate approach only shown by the grey segment, and the SNPs discovered by MultiPhen only illustrated by the black segment. The bars labelled ALL2 and ALL3 combine results across analyses on all combinations of two and three lipid traits, respectively, while ALL combines the results across the analyses of all 2, 3 and 4 combinations of the traits. A complete breakdown of these results is presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s018" target="_blank">Tables S5</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s019" target="_blank">S6</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s020" target="_blank">S7</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s021" target="_blank">S8</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s022" target="_blank">S9</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s023" target="_blank">S10</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s024" target="_blank">S11</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s025" target="_blank">S12</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s026" target="_blank">S13</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s027" target="_blank">S14</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s028" target="_blank">S15</a>.</p

The correlation structure between pairs of lipids.

<p>The left panel shows the correlation structure between total cholesterol (CHOL) and low-density lipoprotein (LDL) in 5655 individuals from the Northern Finland Birth Cohort 1966. Each circle depicts the value of CHOL (X-axis) and LDL (Y-axis) in mmol/L for each individual. The right panel shows the correlation structure between low-density lipoprotein (LDL) and high-density lipoprotein (HDL), in mmol/L, in the same individuals. The arrows in each plot show the direction of effect of a variant affecting only CHOL or only HDL, such that the genotypes of individuals underlying each plotted point are more likely to contain risk alleles for the labelled lipid moving through the points in the direction of the arrow. The diagonal arrows are based on the Friedewald Formula (Friedewald.72). The arrows indicate that effects of variants can be in very different directions in the 2-dimensional spaces shown; the aim of modelling and testing linear combinations of phenotypes is to capture effects in any direction.</p

Behaviour of the different methods under the null.

<p>This table relates to the simulation study to test the type 1 error rates of MultiPhen, CCA, and the univariate approach, described in the text. The elements of the table show the number of results with <i>P</i><1e^–5 in the scenario described by the corresponding row and column (which give the minor allele frequencies) headers. Since 100000 replicates of SNP-phenotype associations were simulated under the null hypothesis of no association, the expectation for all elements of the table is 1; those with >1 indicating inflation of the type 1 error rate. Simulations with MAF = 30%, 0.5% were performed on a sample size of N = 5000. For the full results see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s001" target="_blank">Figures S1</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s008" target="_blank">S8</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s014" target="_blank">Table S1</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0034861#pone.0034861.s016" target="_blank">S3</a>.</p

The power of MultiPhen in different scenarios of effect and correlation between phenotypes.

<p>Power results based on simulations described in the text for MultiPhen (red lines) and the standard single-phenotype approach (black lines). Left panel: causal variant explains 0.5% of phenotypic variance of both phenotypes. Middle panel: causal variant explains 0.5% on the phenotypic variance of the first phenotype and 0.1% of the variance in the second phenotype. Right panel: causal variant explains 0.5% of phenotypic variance of the first phenotype and 0% of the second phenotype.</p

Local association plots.

<p>Panels show the local POE association P-values for the <i>KCNK9</i> (left panel) and <i>SLC2A10</i> (right panel) loci.</p

Replication of the 6 discovery SNPs in trios (or parent-offspring pairs).

<p>For each target SNP, in each family we searched for trios (or parent-offspring pairs) with heterozygous offspring and determined the parent of origin of the alleles (whenever possible). From each family at most one heterozygous offspring with known parental origin was then collected and grouped according to the parental origin of the alleles. The equality of phenotypic means in the two groups was tested using a Student t-test (“P-value for beta difference column”). The difference between the phenotypic means were meta-analysed using inverse-variance weighting. Table notations: “beta meta” and “P meta”: meta-analysis estimate of beta (coded paternal) - beta (coded maternal) effect size differences and the corresponding P-value, “N meta”: total number of heterozygous offspring with (coded-maternal/other-paternal), (coded-paternal/other-maternal) genotypes, respectively.</p