Additional file 2: Table S9. of Shared genetic influences between dimensional ASD and ADHD symptoms during child and adolescent development

Pathway-based dissection of additive genetic variance in SDQ-ADHD and SCDC scores according to 50 molecular signatures database hallmark gene set collections. (XLSX 20 kb

Additional file 1: of Shared genetic influences between dimensional ASD and ADHD symptoms during child and adolescent development

Additional note. Selection of SDQ-ADHD measures. Additional note. Meta-analysis of correlated test statistics from pathway analysis. Additional note. Additional references. Additional note. Web resources. Table S1. Descriptives of SDQ-ADHD and SCDC scores in ALSPAC. Table S2. Phenotypic correlations of SDQ-ADHD scores in ALSPAC. Table S3. Phenotypic correlations of SCDC scores in ALSPAC. Table S4. Univariate GREML of SDQ-ADHD scores in ALSPAC. Table S5. Univariate GREML of SCDC scores in ALSPAC. Table S6. Bivariate GREML of SDQ-ADHD scores in ALSPAC. Table S7. Bivariate GREML of SCDC scores in ALSPAC. Table S8. Bivariate GREML and Pearson correlations of SDQ-ADHD and SCDC scores in ALSPAC. Table S10. Association between ADHD polygenic scores and SDQ-ADHD scores in ALSPAC. Table S11. Association between ASD polygenic scores and SDQ-ADHD scores in ALSPAC. Table S12. Association between ADHD polygenic scores and SCDC scores in ALSPAC. (DOCX 92 kb

Histogram of allele score, with linear relationships between SATS z-scores and the allele score superimposed.

<p>The unweighted allele score is created from three SNPs rs9320913, rs11584700 and rs4851266. Each unit increase in the allele score corresponds to an individual having an additional educational attainment increasing allele. The density for the allele score taking the value 6 is 0.0016, which is too small to be visible in this figure. The linear relationships with 95%CIs from our regressions of SATS z-scores on allele score are superimposed. The English regression is represented by a black line with grey 95%CI, and mathematics by a grey line with black 95%CI.</p

Relationships between SATS z-scores and unweighted allele score within the ALSPAC study.

<p>All models include sex and age as covariables.</p

Overlay histograms showing z-scores for English and mathematics stratified by sex within the ALSPAC study.

<p>Boys’ results in grey; girls’ results in white. Girls exhibit an average 0.433 SD (95%CI 0.395, 0.470), p<10⁻¹⁰ advantage over boys in English, and attain more similar exam results in mathematics with boys exhibiting an average 0.042 SD (95%CI 0.004, 0.080), p = 0.0303 advantage over girls in mathematics.</p

LR asymmetry genes are associated with relative hand skill (meta-analysis of cohorts 1–3).

<p>We've listed the ten lowest gene <i>P</i> values that are also within one of the four enriched phenotypes from <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003751#pgen-1003751-t004" target="_blank"><b>Table 4</b></a> in the RD meta-analysis. MAF = minor allele frequency, β = effect size of each copy of the minor allele, in standard deviations.</p

The intronic marker rs7182874 (ancestral allele = C; derived, minor allele = T) within the gene <i>PCSK6</i> on chromosome 15 is associated with relative hand skill in individuals with reading disability.

<p>β = effect size of each copy of the minor allele in standard deviations, S.E. = Standard Error.</p

GWAS study design.

<p>Three cohorts with reading disability and a further general population cohort were genotyped and tested after imputation for association with relative hand skill.</p

Investigating the shared genetics of non-syndromic cleft lip/palate and facial morphology

<div><p>There is increasing evidence that genetic risk variants for non-syndromic cleft lip/palate (nsCL/P) are also associated with normal-range variation in facial morphology. However, previous analyses are mostly limited to candidate SNPs and findings have not been consistently replicated. Here, we used polygenic risk scores (PRS) to test for genetic overlap between nsCL/P and seven biologically relevant facial phenotypes. Where evidence was found of genetic overlap, we used bidirectional Mendelian randomization (MR) to test the hypothesis that genetic liability to nsCL/P is causally related to implicated facial phenotypes. Across 5,804 individuals of European ancestry from two studies, we found strong evidence, using PRS, of genetic overlap between nsCL/P and philtrum width; a 1 S.D. increase in nsCL/P PRS was associated with a 0.10 mm decrease in philtrum width (95% C.I. 0.054, 0.146; P = 2x10^-5). Follow-up MR analyses supported a causal relationship; genetic variants for nsCL/P homogeneously cause decreased philtrum width. In addition to the primary analysis, we also identified two novel risk loci for philtrum width at 5q22.2 and 7p15.2 in our Genome-wide Association Study (GWAS) of 6,136 individuals. Our results support a liability threshold model of inheritance for nsCL/P, related to abnormalities in development of the philtrum.</p></div

Vitamin B-12 Status during Pregnancy and Child’s IQ at Age 8: A Mendelian Randomization Study in the Avon Longitudinal Study of Parents and Children

<div><p>Vitamin B-12 is essential for the development and maintenance of a healthy nervous system. Brain development occurs primarily <em>in utero</em> and early infancy, but the role of maternal vitamin B-12 status during pregnancy on offspring cognitive function is unclear. In this study we assessed the effect of vitamin B-12 status in well-nourished pregnant women on the cognitive ability of their offspring in a UK birth cohort (ALSPAC). We then examined the association of SNPs in maternal genes <em>FUT2</em> (rs492602) and <em>TCN2</em> (rs1801198, rs9606756) that are related to plasma vitamin B-12, with offspring IQ. Observationally, there was a positive association between maternal vitamin B-12 intake and child’s IQ that was markedly attenuated after adjustment for potential confounders (mean difference in offspring IQ score per doubling of maternal B-12 intake, before adjustment: 2.0 (95% CI 1.3, 2.8); after adjustment: 0.7 (95% CI −0.04, 1.4)). Maternal <em>FUT2</em> was weakly associated with offspring IQ: mean difference in IQ per allele was 0.9 (95% CI 0.1, 1.6). The expected effect of maternal vitamin B-12 on offspring IQ, given the relationships between SNPs and vitamin B-12, and SNPs and IQ was consistent with the observational result. Our findings suggest that maternal vitamin B-12 may not have an important effect on offspring cognitive ability. However, further examination of this issue is warranted.</p> </div