Publications

Abstract

BACKGROUND: It is unclear to what extent non-clinical psychotic experiences during childhood and adolescence share underlying aetiological mechanisms with schizophrenia. One candidate mechanism for schizophrenia involves the epigenetic status of the developing fetus, which depends on the internal folate-status of mother and child. Our study examines the relationships between multiple determinants of perinatal folate-status and development of psychotic experiences in adolescence. METHODS: Study participants were up to 5344 mother-child pairs from the Avon Longitudinal Study of Parents and their Children, UK, with information on maternal and/or child MTHFR C677T genotype, maternal folate intake (supplementation at 18/32- weeks gestation; dietary intake at 32- weeks gestation) and psychosis-like symptoms (PLIKS) for children assessed at age 12. RESULTS: Nominal evidence was observed that maternal folate supplementation at 18 weeks increased the odds of PLIKS in children (odds ratio(OR)=1.34; 95%-CI:[1.00;1.76]) and, consistent with this, that children of MTHFR C667T TT homozygous mothers had decreased odds of PLIKS (OR=0.72; 95%CI:[0.50;1.02]; recessive model) with strongest effects in boys (OR=0.44, 95%-CI:[0.22;0.79]; sex-specific p=0.029). None of the reported effects remained significant when corrected for multiple testing. CONCLUSIONS: Overall, this study found no support that maternal/child MTHFR C677T genotype and maternal folate intake during pregnancy contribute to common aetiological pathways that are shared between schizophrenia and non-clinical psychotic symptoms in adolescents, assuming that decreased folate-status increases schizophrenia risk.

Abstract

PURPOSE: Conduct problems and peer effects are among the strongest risk factors for adolescent substance use and problem use. However, it is unclear to what extent the effects of conduct problems and peer behavior interact, and whether adolescents' capacity to refuse the offer of substances may moderate such links. This study was conducted to examine relationships between conduct problems, close friends' substance use, and refusal assertiveness with adolescents' alcohol use problems, tobacco, and marijuana use. METHODS: We studied a population-based sample of 1,237 individuals from the Cardiff Study of All Wales and North West of England Twins aged 11-18 years. Adolescent and mother-reported information was obtained. Statistical analyses included cross-sectional and prospective logistic regression models and family-based permutations. RESULTS: Conduct problems and close friends' substance use were associated with increased adolescents' substance use, whereas refusal assertiveness was associated with lower use of cigarettes, alcohol, and marijuana. Peer substance use moderated the relationship between conduct problems and alcohol use problems, such that conduct problems were only related to increased risk for alcohol use problems in the presence of substance-using friends. This effect was found in both cross-sectional and prospective analyses and confirmed using the permutation approach. CONCLUSIONS: Reduced opportunities for interaction with alcohol-using peers may lower the risk of alcohol use problems in adolescents with conduct problems.

Abstract

OBJECTIVE: Plasma adiponectin is strongly associated with various components of metabolic syndrome, type 2 diabetes and cardiovascular outcomes. Concentrations are highly heritable and differ between men and women. We therefore aimed to investigate the genetics of plasma adiponectin in men and women. METHODS: We combined genome-wide association scans of three population-based studies including 4659 persons. For the replication stage in 13795 subjects, we selected the 20 top signals of the combined analysis, as well as the 10 top signals with p-values less than 1.0 x 10(-4) for each the men- and the women-specific analyses. We further selected 73 SNPs that were consistently associated with metabolic syndrome parameters in previous genome-wide association studies to check for their association with plasma adiponectin. RESULTS: The ADIPOQ locus showed genome-wide significant p-values in the combined (p=4.3 x 10(-24)) as well as in both women- and men-specific analyses (p=8.7 x 10(-17) and p=2.5 x 10(-11), respectively). None of the other 39 top signal SNPs showed evidence for association in the replication analysis. None of 73 SNPs from metabolic syndrome loci exhibited association with plasma adiponectin (p>0.01). CONCLUSIONS: We demonstrated the ADIPOQ gene as the only major gene for plasma adiponectin, which explains 6.7% of the phenotypic variance. We further found that neither this gene nor any of the metabolic syndrome loci explained the sex differences observed for plasma adiponectin. Larger studies are needed to identify more moderate genetic determinants of plasma adiponectin.

Abstract

The ratio of the lengths of an individual's second to fourth digit (2D:4D) is commonly used as a noninvasive retrospective biomarker for prenatal androgen exposure. In order to identify the genetic determinants of 2D:4D, we applied a genome-wide association approach to 1507 11-year-old children from the Avon Longitudinal Study of Parents and Children (ALSPAC) in whom 2D:4D ratio had been measured, as well as a sample of 1382 12- to 16-year-olds from the Brisbane Adolescent Twin Study. A meta-analysis of the two scans identified a single variant in the LIN28B gene that was strongly associated with 2D:4D (rs314277: p = 4.1 x 10(-8)) and was subsequently independently replicated in an additional 3659 children from the ALSPAC cohort (p = 1.53 x 10(-6)). The minor allele of the rs314277 variant has previously been linked to increased height and delayed age at menarche, but in our study it was associated with increased 2D:4D in the direction opposite to that of previous reports on the correlation between 2D:4D and age at menarche. Our findings call into question the validity of 2D:4D as a simplistic retrospective biomarker for prenatal testosterone exposure.

Abstract

Tooth development is a highly heritable process which relates to other growth and developmental processes, and which interacts with the development of the entire craniofacial complex. Abnormalities of tooth development are common, with tooth agenesis being the most common developmental anomaly in humans. We performed a genome-wide association study of time to first tooth eruption and number of teeth at one year in 4,564 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966) and 1,518 individuals from the Avon Longitudinal Study of Parents and Children (ALSPAC). We identified 5 loci at P<}5x10(-8), and 5 with suggestive association (P{<5x10(-6)). The loci included several genes with links to tooth and other organ development (KCNJ2, EDA, HOXB2, RAD51L1, IGF2BP1, HMGA2, MSRB3). Genes at four of the identified loci are implicated in the development of cancer. A variant within the HOXB gene cluster associated with occlusion defects requiring orthodontic treatment by age 31 years.

Abstract

Objective: Recent genome-wide analysis identified a genetic variant on 5p14.1 (rs4307059), which is associated with risk for autism spectrum disorder. This study investigated whether rs4307059 also operates as a quantitative trait locus underlying a broader autism phenotype in the general population, focusing specifically on the social communication aspect of the spectrum. Method: Study participants were 7,313 children from the Avon Longitudinal Study of Parents and Children. Single-trait and joint-trait genotype associations were investigated for 29 measures related to language and communication, verbal intelligence, social interaction, and behavioral adjustment, assessed between ages 3 and 12 years. Analyses were performed in one-sided or directed mode and adjusted for multiple testing, trait interrelatedness, and random genotype dropout. Results: Single phenotype analyses showed that an increased load of rs4307059 risk allele is associated with stereotyped conversation and lower pragmatic communication skills, as measured by the Children's Communication Checklist (at a mean age of 9.7 years). In addition a trend toward a higher frequency of identification of special educational needs (at a mean age of 11.8 years) was observed. Variation at rs4307059 was also associated with the phenotypic profile of studied traits. This joint signal was fully explained neither by single-trait associations nor by overall behavioral adjustment problems but suggested a combined effect, which manifested through multiple sub-threshold social, communicative, and cognitive impairments. Conclusions: Our results suggest that common variation at 5p14.1 is associated with social communication spectrum phenotypes in the general population and support the role of rs4307059 as a quantitative trait locus for autism spectrum disorder.

Abstract

Although cognitive ability is a highly heritable complex trait, only a few genes have been identified, explaining relatively low proportions of the observed trait variation. This implies that hundreds of genes of small effect may be of importance for cognitive ability. We applied an innovative method in which we tested for the effect of groups of genes defined according to cellular function (functional gene group analysis). Using an initial sample of 627 subjects, this functional gene group analysis detected that synaptic heterotrimeric guanine nucleotide binding proteins (G proteins) play an important role in cognitive ability (P(EMP) = 1.9 x 10(-4)). The association with heterotrimeric G proteins was validated in an independent population sample of 1507 subjects. Heterotrimeric G proteins are central relay factors between the activation of plasma membrane receptors by extracellular ligands and the cellular responses that these induce, and they can be considered a point of convergence, or a "signaling bottleneck." Although alterations in synaptic signaling processes may not be the exclusive explanation for the association of heterotrimeric G proteins with cognitive ability, such alterations may prominently affect the properties of neuronal networks in the brain in such a manner that impaired cognitive ability and lower intelligence are observed. The reported association of synaptic heterotrimeric G proteins with cognitive ability clearly points to a new direction in the study of the genetic basis of cognitive ability.

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.

Abstract

Over recent years small submicroscopic DNA copy-number variants (CNVs) have been highlighted as an important source of variation in the human genome, human phenotypic diversity and disease susceptibility. Consequently, there is a pressing need for the development of methods that allow the efficient, accurate and cheap measurement of genomic copy number polymorphisms in clinical cohorts. We have developed a simple competitive PCR based method to determine DNA copy number which uses the entire genome of a single chimpanzee as a competitor thus eliminating the requirement for competitive sequences to be synthesized for each assay. This results in the requirement for only a single reference sample for all assays and dramatically increases the potential for large numbers of loci to be analysed in multiplex. In this study we establish proof of concept by accurately detecting previously characterized mutations at the PARK2 locus and then demonstrating the potential of quantitative interspecies competitive PCR (qicPCR) to accurately genotype CNVs in association studies by analysing chromosome 22q11 deletions in a sample of previously characterized patients and normal controls.

Abstract

Using parametric and nonparametric techniques, our study investigated the presence of single locus and pairwise effects between 20 markers of the Genetic Analysis Workshop 15 (GAW15) North American Rheumatoid Arthritis Consortium (NARAC) candidate gene data set (Problem 2), analyzing 463 independent patients and 855 controls. Specifically, our work examined the correspondence between logistic regression (LR) analysis of single-locus and pairwise interaction effects, and random forest (RF) single and joint importance measures. For this comparison, we selected small but stable RFs (500 trees), which showed strong correlations (r~0.98) between their importance measures and those by RFs grown on 5000 trees. Both RF importance measures captured most of the LR single-locus and pairwise interaction effects, while joint importance measures also corresponded to full LR models containing main and interaction effects. We furthermore showed that RF measures were particularly sensitive to data imputation. The most consistent pairwise effect on rheumatoid arthritis was found between two markers within MAP3K7IP2/SUMO4 on 6q25.1, although LR and RFs assigned different significance levels. Within a hypothetical two-stage design, pairwise LR analysis of all markers with significant RF single importance would have reduced the number of possible combinations in our small data set by 61%, whereas joint importance measures would have been less efficient for marker pair reduction. This suggests that RF single importance measures, which are able to detect a wide range of interaction effects and are computationally very efficient, might be exploited as pre-screening tool for larger association studies. Follow-up analysis, such as by LR, is required since RFs do not indicate highrisk genotype combinations.

Abstract

Rheumatoid arthritis is the most common systematic autoimmune disease and its etiology is believed to have both strong genetic and environmental components. We demonstrate the utility of including genetic and clinical phenotypes as covariates within a linkage analysis framework to search for rheumatoid arthritis susceptibility loci. The raw genotypes of 1302 affected relative pairs were combined from four large family-based samples (North American Rheumatoid Arthritis Consortium, United Kingdom, European Consortium on Rheumatoid Arthritis Families, and Canada). The familiality of the clinical phenotypes was assessed. The affected relative pairs were subjected to autosomal multipoint affected relative-pair linkage analysis. Covariates were included in the linkage analysis to take account of heterogeneity within the sample. Evidence of familiality was observed with age at onset (p <} 0.001) and rheumatoid factor (RF) IgM (p {< 0.001), but not definite erosions (p = 0.21). Genome-wide significant evidence for linkage was observed on chromosome 6. Genome-wide suggestive evidence for linkage was observed on chromosomes 13 and 20 when conditioning on age at onset, chromosome 15 conditional on gender, and chromosome 19 conditional on RF IgM after allowing for multiple testing of covariates.

Abstract

We have used the genome-wide marker genotypes from Genetic Analysis Workshop 15 Problem 2 to explore joint evidence for genetic linkage to rheumatoid arthritis across several samples. The data consisted of four high-density genome scans on samples selected for rheumatoid arthritis. We cleaned the data, removed intermarker linkage disequilibrium, and assembled the samples onto a common genetic map using genome sequence positions as a reference for map interpolation. The individual studies were combined first at the genotype level (mega-analysis) prior to a multipoint linkage analysis on the combined sample, and second using the genome scan meta-analysis method after linkage analysis of each sample. The two approaches were compared, and give strong support to the HLA locus on chromosome 6 as a susceptibility locus. Other regions of interest include loci on chromosomes 11, 2, and 12.

Abstract

Genome-wide association studies using thousands to hundreds of thousands of single nucleotide polymorphism (SNP) markers and region-wide association studies using a dense panel of SNPs are already in use to identify disease susceptibility genes and to predict disease risk in individuals. Because these tasks become increasingly important, three different data sets were provided for the Genetic Analysis Workshop 15, thus allowing examination of various novel and existing data mining methods for both classification and identification of disease susceptibility genes, gene by gene or gene by environment interaction. The approach most often applied in this presentation group was random forests because of its simplicity, elegance, and robustness. It was used for prediction and for screening for interesting SNPs in a first step. The logistic tree with unbiased selection approach appeared to be an interesting alternative to efficiently select interesting SNPs. Machine learning, specifically ensemble methods, might be useful as pre-screening tools for large-scale association studies because they can be less prone to overfitting, can be less computer processor time intensive, can easily include pair-wise and higher-order interactions compared with standard statistical approaches and can also have a high capability for classification. However, improved implementations that are able to deal with hundreds of thousands of SNPs at a time are required.