The CogBIAS longitudinal study protocol: cognitive and genetic factors influencing psychological functioning in adolescence.

BACKGROUND: Optimal psychological development is dependent upon a complex interplay between individual and situational factors. Investigating the development of these factors in adolescence will help to improve understanding of emotional vulnerability and resilience. The CogBIAS longitudinal study (CogBIAS-L-S) aims to combine cognitive and genetic approaches to investigate risk and protective factors associated with the development of mood and impulsivity-related outcomes in an adolescent sample. METHODS: CogBIAS-L-S is a three-wave longitudinal study of typically developing adolescents conducted over 4 years, with data collection at age 12, 14 and 16. At each wave participants will undergo multiple assessments including a range of selective cognitive processing tasks (e.g. attention bias, interpretation bias, memory bias) and psychological self-report measures (e.g. anxiety, depression, resilience). Saliva samples will also be collected at the baseline assessment for genetic analyses. Multilevel statistical analyses will be performed to investigate the developmental trajectory of cognitive biases on psychological functioning, as well as the influence of genetic moderation on these relationships. DISCUSSION: CogBIAS-L-S represents the first longitudinal study to assess multiple cognitive biases across adolescent development and the largest study of its kind to collect genetic data. It therefore provides a unique opportunity to understand how genes and the environment influence the development and maintenance of cognitive biases and provide insight into risk and protective factors that may be key targets for intervention.This work was supported by the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007–2013)/ERC grant agreement no: [324176]

Common etiological architecture underlying reward responsiveness, externally driven eating behaviors, and BMI in childhood: findings from the Gemini twin cohort

BACKGROUND: Studies have reported that impulsivity predicts childhood BMI and that the association is mediated by eating behaviors. One aspect of impulsivity-potentially crucial in the obesity context-is reward responsiveness, which may predispose to responsiveness to palatable food cues. The behavioral susceptibility theory hypothesizes that genetic susceptibility to obesity operates partly via genetically determined differences in appetite regulation. Reward responsiveness may therefore be one of the neuro-endophenotypes that mediates genetic susceptibility to obesity. OBJECTIVE: To test whether reward responsiveness, eating behaviors, and child BMI share common genetic architecture. METHODS: We examined reward responsiveness, eating behaviors, and BMI in 5-year-old children from Gemini, a UK birth cohort of 2402 twin pairs born in 2007. All measures were collected by parent report. Reward responsiveness was derived from the Behavioral Approach System. Compulsion to eat and eating for pleasure was measured with the "food responsiveness" scale of the Child Eating Behavior Questionnaire. Wanting to eat in response to environmental food cues was measured with the "external eating" scale of the Dutch Eating Behavior Questionnaire. Maximum-likelihood structural equation modeling was used to establish underlying common genetic and environmental influences. RESULTS: There were significant positive phenotypic correlations between all traits except for reward responsiveness and BMI. Genetic factors explained the majority of the association between food responsiveness and external eating (74%, 95% CI: 61, 87), whereas common shared environmental factors explained the majority of the associations between reward responsiveness with both food responsiveness (55%, 95% CI: 20, 90) and external eating (70%, 95% CI: 39, 100). CONCLUSIONS: Our study demonstrates the importance of common environmental factors in the shared etiology between reward responsiveness and childhood eating behaviors. However, the common etiology underlying both reward responsiveness and BMI is unclear, as there was no phenotypic correlation between reward responsiveness and BMI at this age. Further longitudinal research needs to detangle this complex relationship throughout development

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries