FUT2 secretor genotype and susceptibility to infections and chronic conditions in the ALSPAC cohort

Background: The FUT2 (fucosyltransferase 2) gene encodes alpha (1,2) fucosyltransferase, which determines blood group secretor status. Being homozygous for the inactive "non-secretor" rs601338(A) allele appears to confer resistance to certain infections (e.g. Norovirus, Rotavirus and Helicobacter pylori) and susceptibility to others (e.g. Haemophilus influenza and Streptococcus pneumonia). Non-secretors also have an increased risk of type 1 diabetes and inflammatory bowel disease. We aimed to determine the association of the FUT2 secretor genotype with infections and chronic conditions in the population-based Avon Longitudinal Study of Parents and Children (ALSPAC). Methods: This study included 7,582 pregnant women from the ALSPAC pregnancy cohort. Personal history of infections (measles, mumps, chicken pox, whooping cough, cold sores, meningitis, genital herpes, gonorrhea and urinary infections) and chronic conditions (kidney disease, hypertension, diabetes, rheumatism, arthritis, psoriasis, hay fever, asthma, eczema and various allergies) were self-reported by standardized questionnaire. FUT2 secretor status was determined from the rs601338 genotype. Results: Overall, 1920 women (25.3%) were homozygous for the FUT2 non-secretor allele (AA). Secretor status was associated with mumps, with 68% of non-secretors experiencing this infection, compared to 48% of secretors (RR, 1.40; 95% CI, 1.34-1.46; p<0.0001). A weaker association was observed for measles infection (76% vs. 72%; RR, 1.05; 95% CI, 1.02-1.09; p=0.0008). Non-secretors also experienced a 39% increased risk of kidney disease (5.4% vs. 3.9%; RR, 1.39; 95% CI, 1.11-1.75; p=0.004). For some conditions, including gonorrhea and arthritis, FUT2 heterozygosity (GA) appeared to confer an intermediate phenotype. There was no strong evidence of association between FUT2 secretor status and other infections or chronic conditions, although statistical power was limited for rare outcomes. Conclusion: Our results identify an association between FUT2 secretor status and kidney disease, and confirm a recently reported association with susceptibility to mumps infection. The clinical implications of these associations warrant further investigation.

The MR-Base platform supports systematic causal inference across the human phenome

Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.

Age 23 years + oral health questionnaire in Avon Longitudinal Study of Parents and Children

Oral health data in large longitudinal cohort studies is rarely collected at multiple time-points. This type of data is important for assessing oral health trajectories and their determinants. This data resource includes self-report questionnaire data on up to 4,222 young adults at approximately 23 years of age from the Avon Longitudinal Study of Parents and Children (ALSPAC). The resource includes questions on dental attendance, tooth restorations and extractions, third molars (wisdom teeth) and mouth ulcers. This round of data collection follows on from similar questionnaires at ages 7, 10 and 17 years. The ALSPAC study provides an opportunity to combine this oral health data with extensive phenotype, genetic, epigenetic and metabolomic data from the participants, their mothers and fathers.

Age 23 years + oral health questionnaire in Avon Longitudinal Study of Parents and Children

Oral health data in large longitudinal cohort studies is rarely collected at multiple time-points. This type of data is important for assessing oral health trajectories and their determinants. This data resource includes self-report questionnaire data on up to 4,222 young adults at approximately 23 years of age from the Avon Longitudinal Study of Parents and Children (ALSPAC). The resource includes questions on dental attendance, tooth restorations and extractions, third molars (wisdom teeth) and mouth ulcers. It follows on from similar questionnaires at ages 7, 10 and 17 years. The ALSPAC study includes extensive phenotype, genetic, epigenetic and metabolomic data from the participants included in this questionnaire plus their mothers and fathers.

Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference

Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.

Genetic architecture: the shape of the genetic contribution to human traits and disease

Genetic architecture describes the characteristics of genetic variation that are responsible for heritable phenotypic variability. It depends on the number of genetic variants affecting a trait, their frequencies in the population, the magnitude of their effects and their interactions with each other and the environment. Defining the genetic architecture of a complex trait or disease is central to the scientific and clinical goals of human genetics, which are to understand disease aetiology and aid in disease screening, diagnosis, prognosis and therapy. Recent technological advances have enabled genome-wide association studies and emerging next-generation sequencing studies to begin to decipher the nature of the heritable contribution to traits and disease. Here, we describe the types of genetic architecture that have been observed, how architecture can be measured and why an improved understanding of genetic architecture is central to future advances in the field.

Using Y-Chromosomal Haplogroups in Genetic Association Studies and Suggested Implications

Y-chromosomal (Y-DNA) haplogroups are more widely used in population genetics than in genetic epidemiology, although associations between Y-DNA haplogroups and several traits, including cardiometabolic traits, have been reported. In apparently homogeneous populations defined by principal component analyses, there is still Y-DNA haplogroup variation which will result from population history. Therefore, hidden stratification and/or differential phenotypic effects by Y-DNA haplogroups could exist. To test this, we hypothesised that stratifying individuals according to their Y-DNA haplogroups before testing for associations between autosomal single nucleotide polymorphisms (SNPs) and phenotypes will yield difference in association. For proof of concept, we derived Y-DNA haplogroups from 6537 males from two epidemiological cohorts, Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 5080; 816 Y-DNA SNPs) and the 1958 Birth Cohort (n = 1457; 1849 Y-DNA SNPs), and studied the robust associations between 32 SNPs and body mass index (BMI), including SNPs in or near Fat Mass and Obesity-associated protein (FTO) which yield the strongest effects. Overall, no association was replicated in both cohorts when Y-DNA haplogroups were considered and this suggests that, for BMI at least, there is little evidence of differences in phenotype or SNP association by Y-DNA structure. Further studies using other traits, phenome-wide association studies (PheWAS), other haplogroups and/or autosomal SNPs are required to test the generalisability and utility of this approach.

Mendelian Randomization Analysis Identifies CpG Sites as Putative Mediators for Genetic Influences on Cardiovascular Disease Risk

The extent to which genetic influences on cardiovascular disease risk are mediated by changes in DNA methylation levels has not been systematically explored. We developed an analytical framework that integrates genetic fine mapping and Mendelian randomization with epigenome-wide association studies to evaluate the causal relationships between methylation levels and 14 cardiovascular disease traits. We identified ten genetic loci known to influence proximal DNA methylation which were also associated with cardiovascular traits after multiple-testing correction. Bivariate fine mapping provided evidence that the individual variants responsible for the observed effects on cardiovascular traits at the ADCY3 and ADIPOQ loci were potentially mediated through changes in DNA methylation, although we highlight that we are unable to reliably separate causality from horizontal pleiotropy. Estimates of causal effects were replicated with results from large-scale consortia. Genetic variants and CpG sites identified in this study were enriched for histone mark peaks in relevant tissue types and gene promoter regions. Integrating our results with expression quantitative trait loci data, we provide evidence that variation at these regulatory regions is likely to also influence gene expression levels at these loci.

Low-Frequency Synonymous Coding Variation in CYP2R1 Has Large Effects on Vitamin D Levels and Risk of Multiple Sclerosis

Vitamin D insufficiency is common, correctable, and influenced by genetic factors, and it has been associated with risk of several diseases. We sought to identify low-frequency genetic variants that strongly increase the risk of vitamin D insufficiency and tested their effect on risk of multiple sclerosis, a disease influenced by low vitamin D concentrations. We used whole-genome sequencing data from 2,619 individuals through the UK10K program and deep-imputation data from 39,655 individuals genotyped genome-wide. Meta-analysis of the summary statistics from 19 cohorts identified in CYP2R1 the low-frequency (minor allele frequency = 2.5%) synonymous coding variant g.14900931G>A (p.Asp120Asp) (rs117913124[A]), which conferred a large effect on 25-hydroxyvitamin D (25OHD) levels (-0.43 SD of standardized natural log-transformed 25OHD per A allele; p value = 1.5 × 10-88). The effect on 25OHD was four times larger and independent of the effect of a previously described common variant near CYP2R1. By analyzing 8,711 individuals, we showed that heterozygote carriers of this low-frequency variant have an increased risk of vitamin D insufficiency (odds ratio [OR] = 2.2, 95% confidence interval [CI] = 1.78-2.78, p = 1.26 × 10-12). Individuals carrying one copy of this variant also had increased odds of multiple sclerosis (OR = 1.4, 95% CI = 1.19-1.64, p = 2.63 × 10-5) in a sample of 5,927 case and 5,599 control subjects. In conclusion, we describe a low-frequency CYP2R1 coding variant that exerts the largest effect upon 25OHD levels identified to date in the general European population and implicates vitamin D in the etiology of multiple sclerosis.

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10-8) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.

Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study

IMPORTANCE

The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.

OBJECTIVE

To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.

DATA SOURCES

Genomewide association studies (GWAS) published up to January 15, 2015.

STUDY SELECTION

GWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.

DATA EXTRACTION AND SYNTHESIS

Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.

MAIN OUTCOMES AND MEASURES

Odds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.

RESULTS

Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).

CONCLUSIONS AND RELEVANCE

It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Screening for familial hypercholesterolaemia in childhood: Avon Longitudinal Study of Parents and Children (ALSPAC)

BACKGROUND AND AIMS

Familial hypercholesterolaemia (FH) is an autosomal-dominant disease with frequency of 1/500 to 1/250 that leads to premature coronary heart disease. New approaches to identify FH mutation-carriers early are needed to prevent premature cardiac deaths. In a cross-sectional study of the Avon Longitudinal Study of Parents and Children (ALSPAC), we evaluated the biochemical thresholds for FH screening in childhood, and modelled a two-stage biochemical and sequencing screening strategy for FH detection.

METHODS

From 5083 ALSPAC children with cholesterol measurement at age nine years, FH genetic diagnosis was performed in 1512 individuals, using whole-genome or targeted sequencing of known FH-causing genes. Detection rate (DR) and false-positive rate (FPR) for proposed screening thresholds (total-cholesterol > 1.53, or LDL-C > 1.84 multiples of the median (MoM)) were assessed.

RESULTS

Six of 1512 sequenced individuals had an FH-causing mutation of whom five had LDL-C > 1.84 MoM, giving a verification-bias corrected DR of 62.5% (95% CI: 25-92), with a FPR of 0.2% (95% CI: 0.1-0.4). The DR for the TC cut-point of 1.53 MoM was 25% (95% CI: 3.2-65.1) with a FPR of 0.4% (95% CI: 0.2-0.6). We estimated 13 of an expected 20 FH mutation carriers (and 13 of the 20 parental carriers) could be detected for every 10,000 children screened, with false-positives reliably excluded by addition of a next generation sequencing step in biochemical screen-positive samples.

CONCLUSIONS

Proposed cholesterol thresholds for childhood FH screening were less accurate than previously estimated. A sequential strategy of biochemical screening followed by targeted sequencing of FH genes in screen-positive children may help mitigate the higher than previously estimated FPR and reduce wasted screening of unaffected parents.

Association between polygenic risk scores for attention-deficit hyperactivity disorder and educational and cognitive outcomes in the general population

Background

Children with a diagnosis of attention-deficit hyperactivity disorder ADHD) have lower cognitive ability and are at risk of adverse educational outcomes; ADHD genetic risks have been found to predict childhood cognitive ability and other neurodevelopmental traits in the general population; thus genetic risks might plausibly also contribute to cognitive ability later in development and to educational underachievement.

Methods

We generated ADHD polygenic risk scores in the Avon Longitudinal Study of Parents and Children participants (maximum N : 6928 children and 7280 mothers) based on the results of a discovery clinical sample, a genome-wide association study of 727 cases with ADHD diagnosis and 5081 controls. We tested if ADHD polygenic risk scores were associated with educational outcomes and IQ in adolescents and their mothers.

Results

High ADHD polygenic scores in adolescents were associated with worse educational outcomes at Key Stage 3 [national tests conducted at age 13-14 years; β = -1.4 (-2.0 to -0.8), P  = 2.3 × 10 -6 ), at General Certificate of Secondary Education exams at age 15-16 years (β = -4.0 (-6.1 to -1.9), P  = 1.8 × 10 -4 ], reduced odds of sitting Key Stage 5 examinations at age 16-18 years [odds ratio (OR) = 0.90 (0.88 to 0.97), P  = 0.001] and lower IQ scores at age 15.5 [β = -0.8 (-1.2 to -0.4), P  = 2.4 × 10 -4 ]. Moreover, maternal ADHD polygenic scores were associated with lower maternal educational achievement [β = -0.09 (-0.10 to -0.06), P  = 0.005] and lower maternal IQ [β = -0.6 (-1.2 to -0.1), P  = 0.03].

Conclusions

ADHD diagnosis risk alleles impact on functional outcomes in two generations (mother and child) and likely have intergenerational environmental effects.

Prospective associations between problematic eating attitudes in midchildhood and the future onset of adolescent obesity and high blood pressure

BACKGROUND

Clinically diagnosed eating disorders may have adverse cardiometabolic consequences, including overweight or obesity and high blood pressure. However, the link between problematic eating attitudes in early adolescence, which can lead to disordered eating behaviors, and future cardiometabolic health is, to our knowledge, unknown.

OBJECTIVE

We assessed whether variations in midchildhood eating attitudes influence the future development of overweight or obesity and high blood pressure.

DESIGN

Of 17,046 children who participated in the Promotion of Breastfeeding Intervention Trial (PROBIT), we included 13,557 participants (79.5% response rate) who completed the Children's Eating Attitudes Test (ChEAT) at age 11.5 y and in whom we measured adiposity and blood pressure at ages 6.5, 11.5, and 16 y. We assessed whether ChEAT scores ≥85th percentile (indicative of problematic eating attitudes) compared with scores <85th percentile at age 11.5 y were associated with new-onset overweight, obesity, high systolic blood pressure, or high diastolic blood pressure between midchildhood and early adolescence.

RESULTS

After controlling for baseline sociodemographic confounders, we observed positive associations of problematic eating attitudes at age 11.5 y with new-onset obesity (OR: 2.18; 95% CI: 1.58, 3.02), new-onset high systolic blood pressure (OR: 1.34; 95% CI: 1.05, 1.70), and new-onset high diastolic blood pressure (OR: 1.25; 95% CI: 0.99, 1.58) at age 16 y. After further controlling for body mass index at age 6.5 y, problematic eating attitudes remained positively associated with new-onset obesity (OR: 1.80; 95% CI: 1.28, 2.53); however, associations with new-onset high blood pressure were attenuated (OR: 1.14; 95% CI: 0.89, 1.45 and OR: 1.09; 95% CI: 0.86, 1.39 for new-onset systolic and diastolic blood pressure, respectively).

CONCLUSIONS

Problematic eating attitudes in midchildhood seem to be related to the development of obesity in adolescence, a relatively novel observation with potentially important public health implications for obesity control. PROBIT was registered at clinicaltrials.gov as NCT01561612 and isrctn.com as ISRCTN37687716.

Using Genetic Variation to Explore the Causal Effect of Maternal Pregnancy Adiposity on Future Offspring Adiposity: A Mendelian Randomisation Study

BACKGROUND

It has been suggested that greater maternal adiposity during pregnancy affects lifelong risk of offspring fatness via intrauterine mechanisms. Our aim was to use Mendelian randomisation (MR) to investigate the causal effect of intrauterine exposure to greater maternal body mass index (BMI) on offspring BMI and fat mass from childhood to early adulthood.

METHODS AND FINDINGS

We used maternal genetic variants as instrumental variables (IVs) to test the causal effect of maternal BMI in pregnancy on offspring fatness (BMI and dual-energy X-ray absorptiometry [DXA] determined fat mass index [FMI]) in a MR approach. This was investigated, with repeat measurements, from ages 7 to 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 2,521 to 3,720 for different ages). We then sought to replicate findings with results for BMI at age 6 in Generation R (n = 2,337 for replication sample; n = 6,057 for total pooled sample). In confounder-adjusted multivariable regression in ALSPAC, a 1 standard deviation (SD, equivalent of 3.7 kg/m2) increase in maternal BMI was associated with a 0.25 SD (95% CI 0.21-0.29) increase in offspring BMI at age 7, with similar results at later ages and when FMI was used as the outcome. A weighted genetic risk score was generated from 32 genetic variants robustly associated with BMI (minimum F-statistic = 45 in ALSPAC). The MR results using this genetic risk score as an IV in ALSPAC were close to the null at all ages (e.g., 0.04 SD (95% CI -0.21-0.30) at age 7 and 0.03 SD (95% CI -0.26-0.32) at age 18 per SD increase in maternal BMI), which was similar when a 97 variant generic risk score was used in ALSPAC. When findings from age 7 in ALSPAC were meta-analysed with those from age 6 in Generation R, the pooled confounder-adjusted multivariable regression association was 0.22 SD (95% CI 0.19-0.25) per SD increase in maternal BMI and the pooled MR effect (pooling the 97 variant score results from ALSPAC with the 32 variant score results from Generation R) was 0.05 SD (95%CI -0.11-0.21) per SD increase in maternal BMI (p-value for difference between the two results = 0.05). A number of sensitivity analyses exploring violation of the MR results supported our main findings. However, power was limited for some of the sensitivity tests and further studies with relevant data on maternal, offspring, and paternal genotype are required to obtain more precise (and unbiased) causal estimates.

CONCLUSIONS

Our findings provide little evidence to support a strong causal intrauterine effect of incrementally greater maternal BMI resulting in greater offspring adiposity.

The CHRNA5-A3-B4 Gene Cluster and Smoking: From Discovery to Therapeutics

Genome-wide association studies (GWASs) have identified associations between the CHRNA5-CHRNA3-CHRNB4 gene cluster and smoking heaviness and nicotine dependence. Studies in rodents have described the anatomical localisation and function of the nicotinic acetylcholine receptors (nAChRs) formed by the subunits encoded by this gene cluster. Further investigations that complemented these studies highlighted the variability of individuals' smoking behaviours and their ability to adjust nicotine intake. GWASs of smoking-related health outcomes have also identified this signal in the CHRNA5-CHRNA3-CHRNB4 gene cluster. This insight underpins approaches to strengthen causal inference in observational data. Combining genetic and mechanistic studies of nicotine dependence and smoking heaviness may reveal novel targets for medication development. Validated targets can inform genetic therapeutic interventions for smoking cessation and tobacco-related diseases.

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10-8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10-13), T2D (Rg = -0.27, P = 1.1 × 10-6) and coronary artery disease (Rg = -0.30, P = 6.5 × 10-9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10-4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

Heritability and Genome-Wide Association Analyses of Sleep Duration in Children: The EAGLE Consortium

STUDY OBJECTIVES

Low or excessive sleep duration has been associated with multiple outcomes, but the biology behind these associations remains elusive. Specifically, genetic studies in children are scarce. In this study, we aimed to: (1) estimate the proportion of genetic variance of sleep duration in children attributed to common single nucleotide polymorphisms (SNPs), (2) identify novel SNPs associated with sleep duration in children, and (3) investigate the genetic overlap of sleep duration in children and related metabolic and psychiatric traits.

METHODS

We performed a population-based molecular genetic study, using data form the EArly Genetics and Life course Epidemiology (EAGLE) Consortium. 10,554 children of European ancestry were included in the discovery, and 1,250 children in the replication phase.

RESULTS

We found evidence of significant but modest SNP heritability of sleep duration in children (SNP h² 0.14, 95% CI [0.05, 0.23]) using the LD score regression method. A novel region at chromosome 11q13.4 (top SNP: rs74506765, P = 2.27e-08) was associated with sleep duration in children, but this was not replicated in independent studies. Nominally significant genetic overlap was only found (rG = 0.23, P = 0.05) between sleep duration in children and type 2 diabetes in adults, supporting the hypothesis of a common pathogenic mechanism.

CONCLUSIONS

The significant SNP heritability of sleep duration in children and the suggestive genetic overlap with type 2 diabetes support the search for genetic mechanisms linking sleep duration in children to multiple outcomes in health and disease.

A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Pediatric Cohorts

OBJECTIVE

The aims of this study were to elucidate the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis.

METHOD

Within the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium, genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (<13 years of age) from nine population-based cohorts. SNP-based heritability was estimated in data from the three largest cohorts. Meta-analysis based on genome-wide association (GWA) analyses with SNPs was followed by gene-based association tests, and the overlap in results with a meta-analysis in the Psychiatric Genomics Consortium (PGC) case-control ADHD study was investigated.

RESULTS

SNP-based heritability ranged from 5% to 34%, indicating that variation in common genetic variants influences ADHD symptom scores. The meta-analysis did not detect genome-wide significant SNPs, but three genes, lying close to each other with SNPs in high linkage disequilibrium (LD), showed a gene-wide significant association (p values between 1.46 × 10(-6) and 2.66 × 10(-6)). One gene, WASL, is involved in neuronal development. Both SNP- and gene-based analyses indicated overlap with the PGC meta-analysis results with the genetic correlation estimated at 0.96.

CONCLUSION

The SNP-based heritability for ADHD symptom scores indicates a polygenic architecture, and genes involved in neurite outgrowth are possibly involved. Continuous and dichotomous measures of ADHD appear to assess a genetically common phenotype. A next step is to combine data from population-based and case-control cohorts in genetic association studies to increase sample size and to improve statistical power for identifying genetic variants.

BMI as a Modifiable Risk Factor for Type 2 Diabetes: Refining and Understanding Causal Estimates Using Mendelian Randomization

This study focused on resolving the relationship between BMI and type 2 diabetes. The availability of multiple variants associated with BMI offers a new chance to resolve the true causal effect of BMI on type 2 diabetes; however, the properties of these associations and their validity as genetic instruments need to be considered alongside established and new methods for undertaking Mendelian randomization (MR). We explore the potential for pleiotropic genetic variants to generate bias, revise existing estimates, and illustrate value in new analysis methods. A two-sample MR approach with 96 genetic variants was used with three different analysis methods, two of which (MR-Egger and the weighted median) have been developed specifically to address problems of invalid instrumental variables. We estimate an odds ratio for type 2 diabetes per unit increase in BMI (kg/m(2)) of between 1.19 and 1.38, with the most stable estimate using all instruments and a weighted median approach (1.26 [95% CI 1.17, 1.34]). TCF7L2(rs7903146) was identified as a complex effect or pleiotropic instrument, and removal of this variant resulted in convergence of causal effect estimates from different causal analysis methods. This indicated the potential for pleiotropy to affect estimates and differences in performance of alternative analytical methods. In a real type 2 diabetes-focused example, this study demonstrates the potential impact of invalid instruments on causal effect estimates and the potential for new approaches to mitigate the bias caused.

Collapsed methylation quantitative trait loci analysis for low frequency and rare variants

BACKGROUND

Single variant approaches have been successful in identifying DNA methylation quantitative trait loci (mQTL), although as with complex traits they lack the statistical power to identify the effects from rare genetic variants. We have undertaken extensive analyses to identify regions of low frequency and rare variants that are associated with DNA methylation levels.

METHODS

We used repeated measurements of DNA methylation from five different life stages in human blood, taken from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Variants were collapsed across CpG islands and their flanking regions to identify variants collectively associated with methylation, where no single variant was individually responsible for the observed signal. All analyses were undertaken using the sequence kernel association test.

RESULTS

For loci where no individual variant mQTL was observed based on a single variant analysis, we identified 95 unique regions where the combined effect of low frequency variants (MAF ≤ 5%) provided strong evidence of association with methylation. For loci where there was previous evidence of an individual variant mQTL, a further 3 regions provided evidence of association between multiple low frequency variants and methylation levels. Effects were observed consistently across 5 different time points in the lifecourse and evidence of replication in the TwinsUK and Exeter cohorts was also identified.

CONCLUSION

We have demonstrated the potential of this novel approach to mQTL analysis by analysing the combined effect of multiple low frequency or rare variants. Future studies should benefit from applying this approach as a complementary follow up to single variant analyses.