Study design of the Puerto Rico Neo-Natal Twin Registry.

<p>Study design of the Puerto Rico Neo-Natal Twin Registry.</p

Variance component analysis of asthma-related phenotypes at age 3 years.

<p>584 subjects with zygosity confirmed by DNA testing were used in these models.</p>#<p>A =  additive genetic variance, C =  shared environmental variance, E =  non-shared environmental variance.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068473#pone.0068473-Neale1" target="_blank">[23]</a>.</p><p>*P-value for likelihood ratio χ2 test comparing adjusted model to univariate model.</p><p>∧Early-life environmental tobacco smoke (ETS) defined as intrauterine smoke exposure or cigarette exposure ≥2×/week during the first year of life.</p

Prevalence and resemblance between twins for asthma-related phenotypes at age 3 years.

<p>MZ =  monozygotic, DZ =  dizygotic.</p><p>*584 subjects with zygosity confirmed by DNA testing were used in this analysis.</p

Characteristics of participants at ages 1 and 3 years.

<p>Values are reported as number (%) or mean (SD).</p><p>*By DNA testing available for 584 subjects (292 twin pairs)); prevalence per parental report for 678 subjects at 1yo was the same (240 (35.4%)).</p><p>∧Defined as cigarette smoke exposure ≥2 times/week in first year of life.</p

Variance component analysis of asthma-related phenotypes at age 1 year.

<p>584 subjects with zygosity confirmed by DNA testing were used in these models.</p>#<p>A =  additive genetic variance, C =  shared environmental variance, E =  non-shared environmental variance <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068473#pone.0068473-Neale1" target="_blank">[23]</a>.</p><p>*P-value for likelihood ratio χ2 test comparing adjusted to univariate model.</p><p>∧Early-life environmental tobacco smoke (ETS) defined as intrauterine smoke exposure or cigarette exposure ≥2×/week during the first year of life.</p

Prevalence and resemblance between twins for asthma-related phenotypes at age 1 year.

<p>MZ =  monozygotic, DZ =  dizygotic.</p><p>*584 subjects with zygosity confirmed by DNA testing were used in this analysis.</p

ACE model for calculating genetic and environmental influence from twin correlations.[<b>23</b>]

<p>ACE model for calculating genetic and environmental influence from twin correlations.<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068473#pone.0068473-Neale1" target="_blank">[<b>23</b>]</a></p

Overlap between SWAN scores and Resting-State functional MRI samples.

<p>This figure shows the sample size of the ADHD and QTIM studies. Individuals who exhibited gross motion during resting-state fMRI (N = 8), and siblings of a complete twin pair (n = 27) are not included. The sample used in the current study included those with both a SWAN score and HM measures, comprising two overlapping sub-samples (N = 725 and N = 627) as presented in the grey boxes. Number of monozygotic (MZ) and dizygotic (DZ) twin pairs (which include sib-pairs), and number of singletons are shown for each sub-sample.</p

Structural Equation Model that can disentangle the effects of HM and psychological trait (here impulsivity) on RS-fMRI phenotype.

<p>The RS-fMRI phenotype variance is decomposed into 4 factors (or latent traits). The first one influences HM and the brain phenotype and captures false positive findings induced by HM. The second factor is common to HM, Impulsivity and the MRI phenotype. This source of variance can be regressed out by HM regression thus reducing power of detecting some brain changes associated with Impulsivity. The third factor influences Impulsivity and the RS-fMRI phenotype, it is conserved after HM regression. Finally the last latent factor is unique to the imaging phenotype and gathers the sources of variance not accounted by the 3 others. The use of twin and family data allows breaking down each of these factors into genetic and environmental components, thus showing light on the genetic structure of the associations.</p