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Abstract

BACKGROUND: Lower cognitive functioning in early childhood has been proposed as a risk factor for depression in later life but its association with depressive symptoms during adolescence has rarely been investigated. Our study examines the relationship between total intelligence quotient (IQ) score at age 8 years, and depressive symptoms at 11, 13, 14 and 17 years. METHOD: Study participants were 5250 children and adolescents from the Avon Longitudinal Study of Parents and their Children (ALSPAC), UK, for whom longitudinal data on depressive symptoms were available. IQ was assessed with the Wechsler Intelligence Scale for Children III, and self-reported depressive symptoms were measured with the Short Mood and Feelings Questionnaire (SMFQ). RESULTS: Multi-level analysis on continuous SMFQ scores showed that IQ at age 8 years was inversely associated with depressive symptoms at age 11 years, but the association changed direction by age 13 and 14 years (age-IQ interaction, p<}0.0001; age squared-IQ interaction, p{<}0.0001) when a higher IQ score was associated with a higher risk of depressive symptoms. This change in IQ effect was also found in relation to pubertal stage (pubertal stage-IQ interaction, 0.00049{

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Abstract

INTRODUCTION: Smoking behaviors, including heaviness of smoking and smoking cessation, are known to be under a degree of genetic influence. The enzyme catechol O-methyltransferase (COMT) is of relevance in studies of smoking behavior and smoking cessation due to its presence in dopaminergic brain regions. While the COMT gene is therefore one of the more promising candidate genes for smoking behavior, some inconsistencies have begun to emerge. METHODS: We explored whether the rs4680 A (Met) allele of the COMT gene predicts increased heaviness of smoking and reduced likelihood of smoking cessation in a large population-based cohort of pregnant women. We further conducted a meta-analysis of published data from community samples investigating the association of this polymorphism with heaviness of smoking and smoking status. RESULTS: In our primary sample, the A (Met) allele was associated with increased heaviness of smoking before pregnancy but not with the odds of continuing to smoke in pregnancy either in the first trimester or in the third trimester. Meta-analysis also indicated modest evidence of association of the A (Met) allele with increased heaviness of smoking but not with persistent smoking. CONCLUSIONS: Our data suggest a weak association between COMT genotype and heaviness of smoking, which is supported by our meta-analysis. However, it should be noted that the strength of evidence for this association was modest. Neither our primary data nor our meta-analysis support an association between COMT genotype and smoking cessation. Therefore, COMT remains a plausible candidate gene for smoking behavior phenotypes, in particular, heaviness of smoking.

Abstract

Background Thirty-two common variants associated with body mass index (BMI) have been identified in genome-wide association studies, explaining ∼1.45% of BMI variation in general population cohorts. We performed a genome-wide association study in a sample of young adults enriched for extremely overweight individuals. We aimed to identify new loci associated with BMI and to ascertain whether using an extreme sampling design would identify the variants known to be associated with BMI in general populations. Methodology/Principal Findings From two large Danish cohorts we selected all extremely overweight young men and women (n = 2,633), and equal numbers of population-based controls (n = 2,740, drawn randomly from the same populations as the extremes, representing ∼212,000 individuals). We followed up novel (at the time of the study) association signals (p<}0.001) from the discovery cohort in a genome-wide study of 5,846 Europeans, before attempting to replicate the most strongly associated 28 SNPs in an independent sample of Danish individuals (n = 20,917) and a population-based cohort of 15-year-old British adolescents (n = 2,418). Our discovery analysis identified SNPs at three loci known to be associated with BMI with genome-wide confidence (P{<}5×10−8; FTO, MC4R and FAIM2). We also found strong evidence of association at the known TMEM18, GNPDA2, SEC16B, TFAP2B, SH2B1 and KCTD15 loci (p{<}0.001), and nominal association (p{<0.05) at a further 8 loci known to be associated with BMI. However, meta-analyses of our discovery and replication cohorts identified no novel associations. Significance Our results indicate that the detectable genetic variation associated with extreme overweight is very similar to that previously found for general BMI. This suggests that population-based study designs with enriched sampling of individuals with the extreme phenotype may be an efficient method for identifying common variants that influence quantitative traits and a valid alternative to genotyping all individuals in large population-based studies, which may require tens of thousands of subjects to achieve similar power.

Abstract

OBJECTIVE: There is overlap between an autistic and hyperactive-inattentive symptomatology when studied cross-sectionally. This study is the first to examine the longitudinal pattern of association between social-communication deficits and hyperactive-inattentive symptoms in the general population, from childhood through adolescence. We explored the interrelationship between trajectories of co-occurring symptoms, and sought evidence for shared prenatal/perinatal risk factors. METHOD: Study participants were 5,383 singletons of white ethnicity from the Avon Longitudinal Study of Parents and Children (ALSPAC). Multiple measurements of hyperactive-inattentive traits (Strengths and Difficulties Questionnaire) and autistic social-communication impairment (Social Communication Disorder Checklist) were obtained between 4 and 17 years. Both traits and their trajectories were modeled in parallel using latent class growth analysis (LCGA). Trajectory membership was subsequently investigated with respect to prenatal/perinatal risk factors. RESULTS: LCGA analysis revealed two distinct social-communication trajectories (persistently impaired versus low-risk) and four hyperactive-inattentive trait trajectories (persistently impaired, intermediate, childhood-limited and low-risk). Autistic symptoms were more stable than those of attention-deficit/hyperactivity disorder (ADHD) behaviors, which showed greater variability. Trajectories for both traits were strongly but not reciprocally interlinked, such that the majority of children with a persistent hyperactive-inattentive symptomatology also showed persistent social-communication deficits but not vice versa. Shared predictors, especially for trajectories of persistent impairment, were maternal smoking during the first trimester, which included familial effects, and a teenage pregnancy. CONCLUSIONS: Our longitudinal study reveals that a complex relationship exists between social-communication and hyperactive-inattentive traits. Patterns of association change over time, with corresponding implications for removing exclusivity criteria for ASD and ADHD, as proposed for DSM-5.

Abstract

OBJECTIVES: Combining the analysis of family-based samples with unrelated individuals can enhance the power of genetic association studies. Various combined analysis techniques have been recently developed; as yet, there have been no comparisons of their power, or robustness to confounding factors. We investigated empirically the power of up to six combined methods using simulated samples of trios and unrelated cases/controls (TDTCC), trios and unrelated controls (TDTC), and affected sibpairs with parents and unrelated cases/controls (ASPFCC). METHODS: We simulated multiplicative, dominant and recessive models with varying risk parameters in single samples. Additionally, we studied false-positive rates and investigated, if possible, the coverage of the true genetic effect (TDTCC). RESULTS/CONCLUSIONS: Under the TDTCC design, we identified four approaches with equivalent power and false-positive rates. Combined statistics were more powerful than single-sample statistics or a pooled chi(2)-statistic when risk parameters were similar in single samples. Adding parental information to the CC part of the joint likelihood increased the power of generalised logistic regression under the TDTC but not the TDTCC scenario. Formal testing of differences between risk parameters in subsamples was the most sensitive approach to avoid confounding in combined analysis. Non-parametric analysis based on Monte-Carlo testing showed the highest power for ASPFCC samples.

Abstract

The adipocyte-derived protein adiponectin is highly heritable and inversely associated with risk of type 2 diabetes mellitus (T2D) and coronary heart disease (CHD). We meta-analyzed 3 genome-wide association studies for circulating adiponectin levels (n = 8,531) and sought validation of the lead single nucleotide polymorphisms (SNPs) in 5 additional cohorts (n = 6,202). Five SNPs were genome-wide significant in their relationship with adiponectin (P<} or =5x10(-8)). We then tested whether these 5 SNPs were associated with risk of T2D and CHD using a Bonferroni-corrected threshold of P{< or =0.011 to declare statistical significance for these disease associations. SNPs at the adiponectin-encoding ADIPOQ locus demonstrated the strongest associations with adiponectin levels (P-combined = 9.2x10(-19) for lead SNP, rs266717, n = 14,733). A novel variant in the ARL15 (ADP-ribosylation factor-like 15) gene was associated with lower circulating levels of adiponectin (rs4311394-G, P-combined = 2.9x10(-8), n = 14,733). This same risk allele at ARL15 was also associated with a higher risk of CHD (odds ratio [OR] = 1.12, P = 8.5x10(-6), n = 22,421) more nominally, an increased risk of T2D (OR = 1.11, P = 3.2x10(-3), n = 10,128), and several metabolic traits. Expression studies in humans indicated that ARL15 is well-expressed in skeletal muscle. These findings identify a novel protein, ARL15, which influences circulating adiponectin levels and may impact upon CHD risk.

Abstract

Peak bone mass achieved in adolescence is a determinant of bone mass in later life. In order to identify genetic variants affecting bone mineral density (BMD), we performed a genome-wide association study of BMD and related traits in 1518 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). We compared results with a scan of 134 adults with high or low hip BMD. We identified associations with BMD in an area of chromosome 12 containing the Osterix (SP7) locus, a transcription factor responsible for regulating osteoblast differentiation (ALSPAC: P = 5.8 x 10(-4); Australia: P = 3.7 x 10(-4)). This region has previously shown evidence of association with adult hip and lumbar spine BMD in an Icelandic population, as well as nominal association in a UK population. A meta-analysis of these existing studies revealed strong association between SNPs in the Osterix region and adult lumbar spine BMD (P = 9.9 x 10(-11)). In light of these findings, we genotyped a further 3692 individuals from ALSPAC who had whole body BMD and confirmed the association in children as well (P = 5.4 x 10(-5)). Moreover, all SNPs were related to height in ALSPAC children, but not weight or body mass index, and when height was included as a covariate in the regression equation, the association with total body BMD was attenuated. We conclude that genetic variants in the region of Osterix are associated with BMD in children and adults probably through primary effects on growth.