Introduction to Special Focus

Early childhood is a period that is marked by rapid changes in development. Exposure to enriched experiences such as positive family interactions, participation in early childhood education, and community engagement can foster healthy development and prevent many behavioral and mental health difficulties. Conversely, young children’s development can be negatively influenced by a variety of risk-factors that have unfortunate long-term outcomes. Given the pervasive impact of behavioral development on young children’s overall developmental outcomes, research examining strategies to enhance young children’s positive behavioral outcomes is needed. The purpose of this paper is to introduce Part 1 of a two part special issue in Perspectives on Early Childhood Psychology and Education that pertains to enhancing young children’s behavioral outcomes. Rationale for the special issue, content of included articles, and special considerations for readers are described

An Intervention Targeting Academic and Behavioral Skill Deficits in Early Childhood: A Case-Study

Early literacy skills are considered prerequisites for early learners to eventually become effective readers (Storch & Whitehurst, 2002). Increasing early literacy skills is often the goal of teachers and schools, but skill acquisition can be hindered due to the bidirectional relationship between behavior difficulties and academic skill deficits. To compound this struggle, there is limited research available on the use of behavioral interventions that exist in conjunction with early academic interventions (Volpe et al., 2012). The goal of the current study was to pilot three emerging early literacy interventions: Fluency Letter Wheel; Letter Flash; and I Do, We Do, You Do. All three interventions were pulled from the Florida Center for Reading Research (FCRR), and target letter sound fluency (LSF). The second objective of this study was to examine an early academic intervention in conjunction with behavior management techniques (i.e., reinforcement and differential attention). One 7-year-old student with a history of academic and behavioral difficulties was examined across 13 individual academic sessions. A brief experimental analysis (BEA) was utilized within an alternating treatments design to identify the most effective academic intervention. A changing criterion design was then used after the I do, We do, You do intervention emerged as the most effective academic intervention. Results indicated that this intervention had moderate effects for increasing skill acquisition. In addition, skill acquisition of LSF was noted to increase from a frustrational range to a grade level instructional range during intervention implementation. Limitations, implications, and future directions of this research are discussed

Addressing Barriers to Universal Screening for Social, Emotional, and Behavioral Risk in Elementary Schools

Early identification of students in need of additional support in the classroom is an important structure for school districts to have in place. Universal screening for social-emotional and behavioral (SEB) risk is one method that schools can use to identify students in need of SEB support and to begin early intervention programing. Unfortunately, recommendations about universal screening and resources for universal screening for SEB risk are limited. As a result, barriers to screening are increased and interventions are delayed – sometimes indefinitely -- for those who need them most. This paper discusses the barriers and challenges experienced by elementary schools (grades K-5) in one school district in the South across a three-year consultative study. This district was supported by the researchers in identifying an appropriate SEB screener, in disseminating the screener, and in ensuring accuracy in its completion. Across the three years, data were evaluated from previous years, and recommendations to improve the district’s screening initiative were made by the lead consultant and school psychology graduate students. Over time, positive changes were noted in screening practices, but it is evident that more work needs to be done. Specific solutions and future implications for early childhood are discussed

Localising Loci underlying Complex Trait Variation Using Regional Genomic Relationship Mapping

The limited proportion of complex trait variance identified in genome-wide association studies may reflect the limited power of single SNP analyses to detect either rare causative alleles or those of small effect. Motivated by studies that demonstrate that loci contributing to trait variation may contain a number of different alleles, we have developed an analytical approach termed Regional Genomic Relationship Mapping that, like linkage-based family methods, integrates variance contributed by founder gametes within a pedigree. This approach takes advantage of very distant (and unrecorded) relationships, and this greatly increases the power of the method, compared with traditional pedigree-based linkage analyses. By integrating variance contributed by founder gametes in the population, our approach provides an estimate of the Regional Heritability attributable to a small genomic region (e.g. 100 SNP window covering ca. 1 Mb of DNA in a 300000 SNP GWAS) and has the power to detect regions containing multiple alleles that individually contribute too little variance to be detectable by GWAS as well as regions with single common GWAS-detectable SNPs. We use genome-wide SNP array data to obtain both a genome-wide relationship matrix and regional relationship (“identity by state" or IBS) matrices for sequential regions across the genome. We then estimate a heritability for each region sequentially in our genome-wide scan. We demonstrate by simulation and with real data that, when compared to traditional (“individual SNP") GWAS, our method uncovers new loci that explain additional trait variation. We analysed data from three Southern European populations and from Orkney for exemplar traits – serum uric acid concentration and height. We show that regional heritability estimates are correlated with results from genome-wide association analysis but can capture more of the genetic variance segregating in the population and identify additional trait loci

Characterisation of Genome-Wide Association Epistasis Signals for Serum Uric Acid in Human Population Isolates

Genome-wide association (GWA) studies have identified a number of loci underlying variation in human serum uric acid (SUA) levels with the SLC2A9 gene having the largest effect identified so far. Gene-gene interactions (epistasis) are largely unexplored in these GWA studies. We performed a full pair-wise genome scan in the Italian MICROS population (n = 1201) to characterise epistasis signals in SUA levels. In the resultant epistasis profile, no SNP pairs reached the Bonferroni adjusted threshold for the pair-wise genome-wide significance. However, SLC2A9 was found interacting with multiple loci across the genome, with NFIA - SLC2A9 and SLC2A9 - ESRRAP2 being significant based on a threshold derived for interactions between GWA significant SNPs and the genome and jointly explaining 8.0% of the phenotypic variance in SUA levels (3.4% by interaction components). Epistasis signal replication in a CROATIAN population (n = 1772) was limited at the SNP level but improved dramatically at the gene ontology level. In addition, gene ontology terms enriched by the epistasis signals in each population support links between SUA levels and neurological disorders. We conclude that GWA epistasis analysis is useful despite relatively low power in small isolated populations

A genome-wide association scan of RR and QT interval duration in 3 European genetically isolated populations:the EUROSPAN project

We set out to identify common genetic determinants of the length of the RR and QT intervals in 2325 individuals from isolated European populations.We analyzed the heart rate at rest, measured as the RR interval, and the length of the corrected QT interval for association with 318 237 single-nucleotide polymorphisms. The RR interval was associated with common variants within GPR133, a G-protein-coupled receptor (rs885389, P=3.9 x 10(-8)). The QT interval was associated with the earlier reported NOS1AP gene (rs2880058, P=2.00 x 10(-10)) and with a region on chromosome 13 (rs2478333, P=4.34 x 10(-8)), which is 100 kb from the closest known transcript LOC730174 and has previously not been associated with the length of the QT interval.Our results suggested an association between the RR interval and GPR133 and confirmed an association between the QT interval and NOS1AP

Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations

Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipid metabolism are being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic beta-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matched metabolite ratios measured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08 x 10(-66). The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1-3. Variants in 3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of three German MI studies. An additional 70 variants across 23 candidate genes involved in sphingolipid-metabolizing pathways also demonstrate association (p = 10(-4) or less). Circulating concentrations of several key components in sphingolipid metabolism are thus under strong genetic control, and variants in these loci can be tested for a role in the development of common cardiovascular, metabolic, neurological, and psychiatric diseases

Bayesian methods for instrumental variable analysis with genetic instruments (‘Mendelian randomization’): example with urate transporter SLC2A9 as an instrumental variable for effect of urate levels on metabolic syndrome

The ‘Mendelian randomization’ approach uses genotype as an instrumental variable to distinguish between causal and non-causal explanations of biomarker–disease associations. Classical methods for instrumental variable analysis are limited to linear or probit models without latent variables or missing data, rely on asymptotic approximations that are not valid for weak instruments and focus on estimation rather than hypothesis testing. We describe a Bayesian approach that overcomes these limitations, using the JAGS program to compute the log-likelihood ratio (lod score) between causal and non-causal explanations of a biomarker–disease association. To demonstrate the approach, we examined the relationship of plasma urate levels to metabolic syndrome in the ORCADES study of a Scottish population isolate, using genotype at six single-nucleotide polymorphisms in the urate transporter gene SLC2A9 as an instrumental variable. In models that allow for intra-individual variability in urate levels, the lod score favouring a non-causal over a causal explanation was 2.34. In models that do not allow for intra-individual variability, the weight of evidence against a causal explanation was weaker (lod score 1.38). We demonstrate the ability to test one of the key assumptions of instrumental variable analysis—that the effects of the instrument on outcome are mediated only through the intermediate variable—by constructing a test for residual effects of genotype on outcome, similar to the tests of ‘overidentifying restrictions’ developed for classical instrumental variable analysis. The Bayesian approach described here is flexible enough to deal with any instrumental variable problem, and does not rely on asymptotic approximations that may not be valid for weak instruments. The approach can easily be extended to combine information from different study designs. Statistical power calculations show that instrumental variable analysis with genetic instruments will typically require combining information from moderately large cohort and cross-sectional studies of biomarkers with information from very large genetic case–control studies