Generalist genes analysis of DNA markers associated with mathematical ability and disability reveals shared influence across ages and abilities

Background The Generalist Genes Hypothesis is based upon quantitative genetic findings which indicate that many of the same genes influence diverse cognitive abilities and disabilities across age. In a recent genome-wide association study of mathematical ability in 10-year-old children, 43 SNP associations were nominated from scans of pooled DNA, 10 of which were validated in an individually genotyped sample. The 4927 children in this genotyped sample have also been studied at 7, 9 and 12 years of age on measures of mathematical ability, as well as on other cognitive and learning abilities. Results Using these data we have explored the Generalist Genes Hypothesis by assessing the association of the available measures of ability at age 10 and other ages with two composite 'SNP-set' scores, formed from the full set of 43 nominated SNPs and the sub-set of 10 SNPs that were previously found to be associated with mathematical ability at age 10. Both SNP sets yielded significant associations with mathematical ability at ages 7, 9 and 12, as well as with reading and general cognitive ability at age 10. Conclusions Although effect sizes are small, our results correspond with those of quantitative genetic research in supporting the Generalist Genes Hypothesis. SNP sets identified on the basis of their associations with mathematical ability at age 10 show associations with mathematical ability at earlier and later ages and show associations of similar magnitude with reading and general cognitive ability. With small effect sizes expected in such complex traits, future studies may be able to capitalise on power by searching for 'generalist genes' using longitudinal and multivariate approaches

Etiological influences on perceptions of parenting: A longitudinal, multi-informant twin study

Children and their parents often differ in their perception of the relationship they share. As this relationship changes developmentally, the nature of these differences may also change. Longitudinal genetic designs can be used to investigate the developmental etiologies of shared and distinct perceptions. In this study, we used longitudinal psychometric models to analyze child and parent reports of negative parenting for 6417 twin pairs from the Twins Early Development Study at ages 9, 12 and 14 years. Within-time cross-reporter correlations, indicating the degree to which children and parents perceived negative parenting behaviors similarly at each age, were moderate (r = .44 − .46). Longitudinal genetic analyses revealed these shared perceptions to be relatively stable during the transition into adolescence, with this stability driven by a combination of children’s genetic factors and family-wide environmental factors. In contrast, child- and parent-specific perceptions of parenting were predominantly age-specific, a developmental pattern underpinned by child genetic factors and a combination of family-wide and unique environmental influences. These results and their implications are discussed in the context of interplay between reciprocal interactions, subjective insight and developmental behavioral change in the parent–child relationship

Bisulfite-based epityping on pooled genomic DNA provides an accurate estimate of average group DNA methylation

BACKGROUND: DNA methylation plays a vital role in normal cellular function, with aberrant methylation signatures being implicated in a growing number of human pathologies and complex human traits. Methods based on the modification of genomic DNA with sodium bisulfite are considered the 'gold-standard' for DNA methylation profiling on genomic DNA; however, they require relatively large amounts of DNA and may be prohibitively expensive when used on the large sample sizes necessary to detect small effects. We propose that a high-throughput DNA pooling approach will facilitate the use of emerging methylomic profiling techniques in large samples. RESULTS: Compared with data generated from 89 individual samples, our analysis of 205 CpG sites spanning nine independent regions of the genome demonstrates that DNA pools can be used to provide an accurate and reliable quantitative estimate of average group DNA methylation. Comparison of data generated from the pooled DNA samples with results averaged across the individual samples comprising each pool revealed highly significant correlations for individual CpG sites across all nine regions, with an average overall correlation across all regions and pools of 0.95 (95% bootstrapped confidence intervals: 0.94 to 0.96). CONCLUSION: In this study we demonstrate the validity of using pooled DNA samples to accurately assess group DNA methylation averages. Such an approach can be readily applied to the assessment of disease phenotypes reducing the time, cost and amount of DNA starting material required for large-scale epigenetic analyses

Applicability of DNA pools on 500 K SNP microarrays for cost-effective initial screens in genomewide association studies

<p>Abstract</p> <p>Background</p> <p>Genetic influences underpinning complex traits are thought to involve multiple quantitative trait loci (QTLs) of small effect size. Detection of such QTL associations requires systematic screening of large numbers of DNA markers within large sample populations. Using pooled DNA on SNP microarrays to screen for allelic frequency differences between groups such as cases and controls (called SNP Microarray and Pooling, or SNP-MaP) has been validated as an efficient solution on both 10 k and 100 k platforms. We demonstrate that this approach can be effectively applied to the truly genomewide Affymetrix GeneChip^®Mapping 500 K Array.</p> <p>Results</p> <p>In comparisons between five independent DNA pools (<it>N </it>~200 per pool) on separate Affymetrix GeneChip^®Mapping 500 K Array sets, we show that, for SNPs with minor allele frequencies > 0.05, the reliability of the rank order of estimated allele frequencies, assessed as the average correlation between allele frequency estimates across the DNA pools, was 0.948 (average mean difference across the five pools = 0.069). Similarly, validity of the SNP-MaP approach was demonstrated by a rank-order correlation of 0.937 (average mean difference = 0.095) between the average DNA pool allele frequency estimates and the allele frequencies of an independent (CEPH) sample of 60 unrelated individually genotyped subjects.</p> <p>Conclusion</p> <p>We conclude that SNP-MaP can be extended for use on the Affymetrix GeneChip^®Mapping 500 K Array, providing a cost-effective, reliable and valid initial screen of 500 K SNP microarrays in genomewide association scans.</p

Do MZ twins have discordant experiences of friendship? : A qualitative hypothesis-generating MZ twin differences study

[This corrects the article DOI: 10.1371/journal.pone.0180521.]

Are genetic risk factors for psychosis also associated with dimension-specific psychotic experiences in adolescence?

Psychosis has been hypothesised to be a continuously distributed quantitative phenotype and disorders such as schizophrenia and bipolar disorder represent its extreme manifestations. Evidence suggests that common genetic variants play an important role in liability to both schizophrenia and bipolar disorder. Here we tested the hypothesis that these common variants would also influence psychotic experiences measured dimensionally in adolescents in the general population. Our aim was to test whether schizophrenia and bipolar disorder polygenic risk scores (PRS), as well as specific single nucleotide polymorphisms (SNPs) previously identified as risk variants for schizophrenia, were associated with adolescent dimension-specific psychotic experiences. Self-reported Paranoia, Hallucinations, Cognitive Disorganisation, Grandiosity, Anhedonia, and Parent-rated Negative Symptoms, as measured by the Specific Psychotic Experiences Questionnaire (SPEQ), were assessed in a community sample of 2,152 16-year-olds. Polygenic risk scores were calculated using estimates of the log of odds ratios from the Psychiatric Genomics Consortium GWAS stage-1 mega-analysis of schizophrenia and bipolar disorder. The polygenic risk analyses yielded no significant associations between schizophrenia and bipolar disorder PRS and the SPEQ measures. The analyses on the 28 individual SNPs previously associated with schizophrenia found that two SNPs in TCF4 returned a significant association with the SPEQ Paranoia dimension, rs17512836 (p-value=2.57x10-4) and rs9960767 (p-value=6.23x10-4). Replication in an independent sample of 16-year-olds (N=3,427) assessed using the Psychotic-Like Symptoms Questionnaire (PLIKS-Q), a composite measure of multiple positive psychotic experiences, failed to yield significant results. Future research with PRS derived from larger samples, as well as larger adolescent validation samples, would improve the predictive power to test these hypotheses further. The challenges of relating adult clinical diagnostic constructs such as schizophrenia to adolescent psychotic experiences at a genetic level are discussed

Polygenic risk for mental disorder reveals distinct association profiles across social behaviour in the general population

Many mental health conditions present a spectrum of social difficulties that overlaps with social behaviour in the general population including shared but little characterised genetic links. Here, we systematically investigate heterogeneity in shared genetic liabilities with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), bipolar disorder (BP), major depression (MD) and schizophrenia across a spectrum of different social symptoms. Longitudinally assessed low-prosociality and peer-problem scores in two UK population-based cohorts (4–17 years; parent- and teacher-reports; Avon Longitudinal Study of Parents and Children(ALSPAC): N ≤ 6,174; Twins Early Development Study(TEDS): N ≤ 7,112) were regressed on polygenic risk scores for disorder, as informed by genome-wide summary statistics from large consortia, using negative binomial regression models. Across ALSPAC and TEDS, we replicated univariate polygenic associations between social behaviour and risk for ADHD, MD and schizophrenia. Modelling variation in univariate genetic effects jointly using random-effect meta-regression revealed evidence for polygenic links between social behaviour and ADHD, ASD, MD, and schizophrenia risk, but not BP. Differences in age, reporter and social trait captured 45–88% in univariate effect variation. Cross-disorder adjusted analyses demonstrated that age-related heterogeneity in univariate effects is shared across mental health conditions, while reporter- and social trait-specific heterogeneity captures disorder-specific profiles. In particular, ADHD, MD, and ASD polygenic risk were more strongly linked to peer problems than low prosociality, while schizophrenia was associated with low prosociality only. The identified association profiles suggest differences in the social genetic architecture across mental disorders when investigating polygenic overlap with population-based social symptoms spanning 13 years of child and adolescent development