Osteoarthritis is a common complex disease imposing a large public-health burden. Here, we performed a genome-wide association study for osteoarthritis, using data across 16.5 million variants from the UK Biobank resource. After performing replication and meta-analysis in up to 30,727 cases and 297,191 controls, we identified nine new osteoarthritis loci, in all of which the most likely causal variant was noncoding. For three loci, we detected association with biologically relevant radiographic endophenotypes, and in five signals we identified genes that were differentially expressed in degraded compared with intact articular cartilage from patients with osteoarthritis. We established causal effects on osteoarthritis for higher body mass index but not for triglyceride levels or genetic predisposition to type 2 diabetes.

Participant overlap can induce overfitting bias into Mendelian randomization (MR) and polygenic risk score (PRS) studies. Here, we evaluated a block jackknife resampling framework for genome-wide association studies (GWAS) and PRS construction to mitigate overfitting bias in MR analyses and implemented this study design in a causal inference setting using data from the UK Biobank. We simulated PRS and MR under three scenarios: (1) using weighted SNP estimates from an external GWAS, (2) using weighted SNP estimates from an overlapping GWAS sample and (3) using a block jackknife resampling framework. Based on a P-value threshold to derive genetic instruments for MR studies (P < 5 × 10-8) and a 10% variance in the exposure explained by all SNPs, block-jackknifing PRS did not suffer from overfitting bias (mean R2 = 0.034) compared with the externally weighted PRS (mean R2 = 0.040). In contrast, genetic instruments derived from overlapping samples explained a higher variance (mean R2 = 0.048) compared with the externally derived score. Overfitting became considerably more severe when using a more liberal P-value threshold to construct PRS (e.g. P < 0.05, overlapping sample PRS mean R2 = 0.103, externally weighted PRS mean R2 = 0.086), whereas estimates using jackknife score remained robust to overfitting (mean R2 = 0.084). Using block jackknife resampling MR in an applied analysis, we examined the effects of body mass index on circulating biomarkers which provided comparable estimates to an externally weighted instrument, whereas the overfitted scores typically provided narrower confidence intervals. Furthermore, we extended this framework into sex-stratified, multivariate and bidirectional settings to investigate the effect of childhood body size on adult testosterone levels.

Rapid postnatal growth is associated with increased risk of childhood adiposity. The aim of this study was to establish whether this pathway is mediated by altered DNA methylation and gene expression. Two distinct cohorts, one preterm (n=121) and one term born (n=6,990), were studied. Exploratory analyses were performed using microarrays to identify differentially expressed genes in whole blood from children defined as "slow" (n=10) compared with "rapid" (n=10) postnatal (term to 12 weeks corrected age) growers. Methylation within the identified TACSTD2 gene was measured in both cohorts, and rs61779296 genotype was determined by Pyrosequencing or imputation and analyzed in relation to body composition at 9-15 years of age. In cohort 1, TACSTD2 expression was inversely correlated with methylation (P=0.016), and both measures were associated with fat mass (expression, P=0.049; methylation, P=0.037). Although associated with gene expression (cohort 1, P=0.008) and methylation (cohort 1, P=2.98×10(-11); cohort 2, P=3.43×10(-15)), rs61779296 was not associated with postnatal growth or fat mass in either cohort following multiple regression analysis. Hence, the lack of association between fat mass and a methylation proxy SNP suggests that reverse causation or confounding may explain the initial association between fat mass and gene regulation. Noncausal methylation patterns may still be useful predictors of later adiposity.

Humans display structural and functional asymmetries in brain organization, strikingly with respect to language and handedness. The molecular basis of these asymmetries is unknown. We report a genome-wide association study meta-analysis for a quantitative measure of relative hand skill in individuals with dyslexia [reading disability (RD)] (n = 728). The most strongly associated variant, rs7182874 (P = 8.68 × 10(-9)), is located in PCSK6, further supporting an association we previously reported. We also confirmed the specificity of this association in individuals with RD; the same locus was not associated with relative hand skill in a general population cohort (n = 2,666). As PCSK6 is known to regulate NODAL in the development of left/right (LR) asymmetry in mice, we developed a novel approach to GWAS pathway analysis, using gene-set enrichment to test for an over-representation of highly associated variants within the orthologs of genes whose disruption in mice yields LR asymmetry phenotypes. Four out of 15 LR asymmetry phenotypes showed an over-representation (FDR ≤ 5%). We replicated three of these phenotypes; situs inversus, heterotaxia, and double outlet right ventricle, in the general population cohort (FDR ≤ 5%). Our findings lead us to propose that handedness is a polygenic trait controlled in part by the molecular mechanisms that establish LR body asymmetry early in development.

Milk intake has been associated with lower blood pressure (BP) in observational studies, and randomized controlled trials suggested that milk-derived tripeptides have BP-lowering effects. Milk intake has also been associated with body mass index (BMI). Nevertheless, it is unclear whether increasing milk consumption would reduce BP in the general population.

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.

Estimated genetic associations with prognosis, or conditional on a phenotype (e.g. disease incidence), may be affected by collider bias, whereby conditioning on the phenotype induces associations between causes of the phenotype and prognosis. We propose a method, 'Slope-Hunter', that uses model-based clustering to identify and utilise the class of variants only affecting the phenotype to estimate the adjustment factor, assuming this class explains more variation in the phenotype than any other variant classes. Simulation studies show that our approach eliminates the bias and outperforms alternatives even in the presence of genetic correlation. In a study of fasting blood insulin levels (FI) conditional on body mass index, we eliminate paradoxical associations of the underweight loci: COBLLI; PPARG with increased FI, and reveal an association for the locus rs1421085 (FTO). In an analysis of a case-only study for breast cancer mortality, a single region remains associated with more pronounced results.

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10-8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

Dietary energy density (DED) does not have a simple linear relationship to fat mass in children, which suggests that some children are more susceptible than others to the effects of DED. Children with the FTO (rs9939609) variant that increases the risk of obesity may have a higher susceptibility to the effects of DED because their internal appetite control system is compromised. We tested the relationship between DED and fat mass in early adolescence and its interaction with FTO variants.

Metformin shows beneficial effects on cardiometabolic health in diabetic individuals. However, the beneficial effects in the general population, especially in non-diabetic individuals are unclear. We aim to estimate the effects of perturbation of seven metformin targets on cardiometabolic health using Mendelian randomization (MR).

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.

Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

Genome-wide association study results have yielded evidence for the association of common genetic variants with crude measures of completed educational attainment in adults. Whilst informative, these results do not inform as to the mechanism of these effects or their presence at earlier ages and where educational performance is more routinely and more precisely assessed. Single nucleotide polymorphisms exhibiting genome-wide significant associations with adult educational attainment were combined to derive an unweighted allele score in 5,979 and 6,145 young participants from the Avon Longitudinal Study of Parents and Children with key stage 3 national curriculum test results (SATS results) available at age 13 to 14 years in English and mathematics respectively. Standardised (z-scored) results for English and mathematics showed an expected relationship with sex, with girls exhibiting an advantage over boys in English (0.433 SD (95%CI 0.395, 0.470), p<10(-10)) with more similar results (though in the opposite direction) in mathematics (0.042 SD (95%CI 0.004, 0.080), p = 0.030). Each additional adult educational attainment increasing allele was associated with 0.041 SD (95%CI 0.020, 0.063), p = 1.79×10(-04) and 0.028 SD (95%CI 0.007, 0.050), p = 0.01 increases in standardised SATS score for English and mathematics respectively. Educational attainment is a complex multifactorial behavioural trait which has not had heritable contributions to it fully characterised. We were able to apply the results from a large study of adult educational attainment to a study of child exam performance marking events in the process of learning rather than realised adult end product. Our results support evidence for common, small genetic contributions to educational attainment, but also emphasise the likely lifecourse nature of this genetic effect. Results here also, by an alternative route, suggest that existing methods for child examination are able to recognise early life variation likely to be related to ultimate educational attainment.

Association studies have identified a number of loci that contribute to an increased body mass index (BMI), the strongest of which is in the first intron of the FTO gene on human chromosome 16q12.2. However, this region is both non-coding and under strong linkage disequilibrium, making it recalcitrant to functional interpretation. Furthermore, the FTO gene is located within a complex cis-regulatory landscape defined by a topologically associated domain that includes the IRXB gene cluster, a trio of developmental regulators. Consequently, at least three genes in this interval have been implicated in the aetiology of obesity.

Observational studies have reported associations between body mass index (BMI) and asthma, but confounding and reverse causality remain plausible explanations. We aim to investigate evidence for a causal effect of BMI on asthma using a Mendelian randomization approach.

Increased adiposity is linked with higher risk for cardiometabolic diseases. We aimed to determine to what extent elevated body mass index (BMI) within the normal weight range has causal effects on the detailed systemic metabolite profile in early adulthood.

Cross-sectional studies have shown that objectively measured physical activity is associated with childhood adiposity, and a strong inverse dose-response association with body mass index (BMI) has been found. However, few studies have explored the extent to which this association reflects reverse causation. We aimed to determine whether childhood adiposity causally influences levels of physical activity using genetic variants reliably associated with adiposity to estimate causal effects.

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Most estimates of this association are affected by endogeneity bias. We use a novel identification strategy exploiting Mendelian Randomization - random germline genetic variation modelled using instrumental variables - to identify the causal effect of BMI on inpatient hospital costs. Using data on over 300,000 individuals, the effect size per person per marginal unit of BMI per year varied according to specification, including £21.22 (95% confidence interval (CI): £14.35-£28.07) for conventional inverse variance weighted models to £18.85 (95% CI: £9.05-£28.65) for penalized weighted median models. Effect sizes from Mendelian Randomization models were larger in most cases than non-instrumental variable multivariable adjusted estimates (£13.47, 95% CI: £12.51-£14.43). There was little evidence of non-linearity. Within-family estimates, intended to address dynastic biases, were imprecise.