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Objective: To estimate the rates of meconium-stained amniotic fluid (AF) and adverse outcome in relation to gestational age and racial group, and to investigate the predictors of meconium-stained AF.Methods: We studied 499,096 singleton births weighing at least 500 g, at 24 or more weeks of gestation, from 1988 to 2000. The predictors of meconium-stained AF from 37 weeks of gestation onward were determined using multiple logistic regression.Results: The crude meconium-stained AF rates in preterm, term, and postterm births were 5.1% (95% confidence interval [CI] 4.9-5.4), 16.5% (95% CI 16.4-16.6), and 27.1% (95% CI 26.5-27.6), respectively; the rates in blacks, South Asians, and whites were 22.6% (95% CI 22.2-23.1), 16.8% (95% CI 16.5-17.1), and 15.7% (95% CI 15.6-15.8), respectively. Independent predictors of meconium-stained AF included being black (odds ratio [OR] 8.4, 95% CI 2.4-28.8), vaginal breech delivery (OR 4.7, 95% CI 4.2-5.3), being South Asian (OR 3.3, 95% CI 1.3-8.3), and being in an advancing week of gestation (OR 1.39, 95% CI 1.38-1.40). More blacks (17.9%, 95% CI 17.3-18.4) and South Asians (11.8%, 95% CI 11.5-12.1) with good outcome and no risk factors for fetal hypoxia had meconium-stained AF than did whites (11.2%, 95% CI 11.1-11.4). Using white neonates born at 40 weeks as reference, the absolute risk of adverse outcome at 41 and 42 weeks were 2% and 5% in whites, 3% and 7%, in South Asians, and 7% and 11% in blacks.Conclusion: Meconium-stained AF rates are different among races and across gestational age, and overall risk of adverse outcomes in meconium stained AF is low.Level Of Evidence: II. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To determine whether key features of systemic lupus erythematosus (SLE), namely, production of non-nuclear antibodies (anti-C1q and anticardiolipin antibodies [aCL]) and depletion of complement components C3 and C4, aggregate in families. In addition, we examined relationships between anti-C1q and C3 and C4 levels. METHODS: The study cohort comprised 1,037 predominantly white (82%) nuclear families in which at least 1 member had SLE. Associations of antibody measurements between probands and their unaffected siblings were examined using parametric and nonparametric analyses, along with associations between unaffected siblings and their parents. The heritability of anti-C1q, C3, and C4 was estimated, and interdependencies between these factors were examined in a regression model accounting for the family structure of the data set. RESULTS: We demonstrated associations between siblings for anti-C1q (odds ratio [OR] 3.74, 95% confidence interval [95% CI] 2.65, 5.28) and IgG and IgM aCL (OR 4.08, 95% CI 1.83, 5.13 and OR 2.06, 95% CI 1.46, 2.91, respectively) and, for anti-C1q, association between unaffected parents and their unaffected offspring (OR 4.34, 95% CI 2.16, 8.72). We also demonstrated significant heritability of anti-C1q, C3, and C4 (approximately 45%). Anti-C1q was negatively associated with C3 and C4 in SLE probands but not in their healthy relatives. CONCLUSION: Non-nuclear antibodies and C3 and C4 cluster within the families of SLE probands, suggesting that specific autoantibody formation is partly genetically determined, even if the total genetic effect in unaffected relatives is insufficient to cause disease. Anti-C1q antibodies accelerate C3 and C4 depletion in patients with SLE but have no effect in the absence of disease. [ABSTRACT FROM AUTHOR]

Evidence on the validity of drug targets from randomized trials is reliable but typically expensive and slow to obtain. In contrast, evidence from conventional observational epidemiological studies is less reliable because of the potential for bias from confounding and reverse causation. Mendelian randomization is a quasi-experimental approach analogous to a randomized trial that exploits naturally occurring randomization in the transmission of genetic variants. In Mendelian randomization, genetic variants that can be regarded as proxies for an intervention on the proposed drug target are leveraged as instrumental variables to investigate potential effects on biomarkers and disease outcomes in large-scale observational datasets. This approach can be implemented rapidly for a range of drug targets to provide evidence on their effects and thus inform on their priority for further investigation. In this review, we present statistical methods and their applications to showcase the diverse opportunities for applying Mendelian randomization in guiding clinical development efforts, thus enabling interventions to target the right mechanism in the right population group at the right time. These methods can inform investigators on the mechanisms underlying drug effects, their related biomarkers, implications for the timing of interventions, and the population subgroups that stand to gain the most benefit. Most methods can be implemented with publicly available data on summarized genetic associations with traits and diseases, meaning that the only major limitations to their usage are the availability of appropriately powered studies for the exposure and outcome and the existence of a suitable genetic proxy for the proposed intervention., Competing Interests: Declaration of interests W.G.H., G.K.H., L.B.K., and D.G. are employed by Novo Nordisk., (Copyright © 2022 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Background and Aims: Understanding of the significant genetic risk factors for Cholangiocarcinoma (CC) remains limited. Polymorphisms in the natural killer cell receptor G2D (NKG2D) gene have been shown to increase risk of CC transformation in patients with Primary Sclerosing Cholangitis (PSC). We present a validation study of NKG2D polymorphisms in CC patients without PSC., Methods: Seven common Single Nucleotide Polymorphisms (SNPs) of the NKG2D gene were genotyped in 164 non-PSC related CC subjects and 257 controls with HaploView. The two SNPs that were positively identified in the previous Scandinavian study, rs11053781 and rs2617167, were included., Results: The seven genotyped SNPs were not associated with risk of CC. Furthermore, haplotype analysis revealed that there was no evidence to suggest that any haplotype differs in frequency between cases and controls ( P  > 0.1)., Conclusion: The common genetic variation in NKG2D does not correlate significantly with sporadic CC risk. This is in contrast to the previous positive findings in the Scandinavian study with PSC-patients. The failure to reproduce the association may reflect an important difference between the pathogenesis of sporadic CC and that of PSC-related CC. Given that genetic susceptibility is likely to be multifaceted and complex, further validation studies that include both sporadic and PSC-related CC are required.

Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function-associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.

Background: We investigated causal effect of completed growth, measured by adult height, on coronary heart disease (CHD), stroke and cardiovascular traits, using instrumental variable (IV) Mendelian randomization meta-analysis., Methods: We developed an allele score based on 69 single nucleotide polymorphisms (SNPs) associated with adult height, identified by the IBCCardioChip, and used it for IV analysis against cardiovascular risk factors and events in 21 studies and 60 028 participants. IV analysis on CHD was supplemented by summary data from 180 height-SNPs from the GIANT consortium and their corresponding CHD estimates derived from CARDIoGRAMplusC4D., Results: IV estimates from IBCCardioChip and GIANT-CARDIoGRAMplusC4D showed that a 6.5-cm increase in height reduced the odds of CHD by 10% [odds ratios 0.90; 95% confidence intervals (CIs): 0.78 to 1.03 and 0.85 to 0.95, respectively],which agrees with the estimate from the Emerging Risk Factors Collaboration (hazard ratio 0.93; 95% CI: 0.91 to 0.94). IV analysis revealed no association with stroke (odds ratio 0.97; 95% CI: 0.79 to 1.19). IV analysis showed that a 6.5-cm increase in height resulted in lower levels of body mass index ( P  < 0.001), triglycerides ( P  < 0.001), non high-density (non-HDL) cholesterol ( P  < 0.001), C-reactive protein ( P  = 0.042), and systolic blood pressure ( P  = 0.064) and higher levels of forced expiratory volume in 1 s and forced vital capacity ( P  < 0.001 for both)., Conclusions: Taller individuals have a lower risk of CHD with potential explanations being that taller people have a better lung function and lower levels of body mass index, cholesterol and blood pressure., (© The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association)

Mendelian randomization (MR) studies typically assess the pathogenic relevance of environmental exposures or disease biomarkers, using genetic variants that instrument these exposures. The approach is gaining popularity-our systematic review reveals a greater than 10-fold increase in MR studies published between 2004 and 2015. When the MR paradigm was first proposed, few biomarker- or exposure-related genetic variants were known, most having been identified by candidate gene studies. However, genome-wide association studies (GWAS) are now providing a rich source of potential instruments for MR analysis. Many early reviews covering the concept, applications and analytical aspects of the MR technique preceded the surge in GWAS, and thus the question of how best to select instruments for MR studies from the now extensive pool of available variants has received insufficient attention. Here we focus on the most common category of MR studies-those concerning disease biomarkers. We consider how the selection of instruments for MR analysis from GWAS requires consideration of: the assumptions underlying the MR approach; the biology of the biomarker; the genome-wide distribution, frequency and effect size of biomarker-associated variants (the genetic architecture); and the specificity of the genetic associations. Based on this, we develop guidance that may help investigators to plan and readers interpret MR studies., (© The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Increased circulating plasma urate concentration is associated with an increased risk of coronary heart disease, but the extent of any causative effect of urate on risk of coronary heart disease is still unclear. In this study, we aimed to clarify any causal role of urate on coronary heart disease risk using Mendelian randomisation analysis., Methods: We first did a fixed-effects meta-analysis of the observational association of plasma urate and risk of coronary heart disease. We then used a conventional Mendelian randomisation approach to investigate the causal relevance using a genetic instrument based on 31 urate-associated single nucleotide polymorphisms (SNPs). To account for potential pleiotropic associations of certain SNPs with risk factors other than urate, we additionally did both a multivariable Mendelian randomisation analysis, in which the genetic associations of SNPs with systolic and diastolic blood pressure, HDL cholesterol, and triglycerides were included as covariates, and an Egger Mendelian randomisation (MR-Egger) analysis to estimate a causal effect accounting for unmeasured pleiotropy., Findings: In the meta-analysis of 17 prospective observational studies (166 486 individuals; 9784 coronary heart disease events) a 1 SD higher urate concentration was associated with an odds ratio (OR) for coronary heart disease of 1·07 (95% CI 1·04-1·10). The corresponding OR estimates from the conventional, multivariable adjusted, and Egger Mendelian randomisation analysis (58 studies; 198 598 individuals; 65 877 events) were 1·18 (95% CI 1·08-1·29), 1·10 (1·00-1·22), and 1·05 (0·92-1·20), respectively, per 1 SD increment in plasma urate., Interpretation: Conventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions., Funding: UK National Institute for Health Research, British Heart Foundation, and UK Medical Research Council., (Copyright © 2016 White et al. Open Access article distributed under the terms of CC BY. Published by Elsevier Ltd.. All rights reserved.)

Over a quarter of drugs that enter clinical development fail because they are ineffective. Growing insight into genes that influence human disease may affect how drug targets and indications are selected. However, there is little guidance about how much weight should be given to genetic evidence in making these key decisions. To answer this question, we investigated how well the current archive of genetic evidence predicts drug mechanisms. We found that, among well-studied indications, the proportion of drug mechanisms with direct genetic support increases significantly across the drug development pipeline, from 2.0% at the preclinical stage to 8.2% among mechanisms for approved drugs, and varies dramatically among disease areas. We estimate that selecting genetically supported targets could double the success rate in clinical development. Therefore, using the growing wealth of human genetic data to select the best targets and indications should have a measurable impact on the successful development of new drugs.

We developed a 65 type 2 diabetes (T2D) variant-weighted gene score to examine the impact on T2D risk assessment in a U.K.-based consortium of prospective studies, with subjects initially free from T2D (N = 13,294; 37.3% women; mean age 58.5 [38-99] years). We compared the performance of the gene score with the phenotypically derived Framingham Offspring Study T2D risk model and then the two in combination. Over the median 10 years of follow-up, 804 participants developed T2D. The odds ratio for T2D (top vs. bottom quintiles of gene score) was 2.70 (95% CI 2.12-3.43). With a 10% false-positive rate, the genetic score alone detected 19.9% incident cases, the Framingham risk model 30.7%, and together 37.3%. The respective area under the receiver operator characteristic curves were 0.60 (95% CI 0.58-0.62), 0.75 (95% CI 0.73 to 0.77), and 0.76 (95% CI 0.75 to 0.78). The combined risk score net reclassification improvement (NRI) was 8.1% (5.0 to 11.2; P = 3.31 × 10(-7)). While BMI stratification into tertiles influenced the NRI (BMI ≤24.5 kg/m(2), 27.6% [95% CI 17.7-37.5], P = 4.82 × 10(-8); 24.5-27.5 kg/m(2), 11.6% [95% CI 5.8-17.4], P = 9.88 × 10(-5); >27.5 kg/m(2), 2.6% [95% CI -1.4 to 6.6], P = 0.20), age categories did not. The addition of the gene score to a phenotypic risk model leads to a potentially clinically important improvement in discrimination of incident T2D., (© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Background: We evaluated germline single nucleotide polymorphisms (SNPs) for association with overall survival (OS) in pazopanib- or sunitinib-treated patients with advanced renal cell carcinoma (aRCC)., Methods: The discovery analysis tested 27 SNPs within 13 genes from a phase III pazopanib trial (N=241, study 1). Suggestive associations were then pursued in two independent datasets: a phase III trial (COMPARZ) comparing pazopanib vs sunitinib (N=729, study 2) and an observational study of sunitinib-treated patients (N=89, study 3)., Results: In study 1, four SNPs showed nominally significant association (P≤0.05) with OS; two of these SNPs (rs1126647, rs4073) in IL8 were associated (P≤0.05) with OS in study 2. Because rs1126647 and rs4073 were highly correlated, only rs1126647 was evaluated in study 3, which also showed association (P≤0.05). In the combined data, rs1126647 was associated with OS after conservative multiple-test adjustment (P=8.8 × 10(-5); variant vs reference allele hazard ratio 1.32, 95% confidence interval: 1.15-1.52), without evidence for heterogeneity of effects between studies or between pazopanib- and sunitinib-treated patients., Conclusions: Variant alleles of IL8 polymorphisms are associated with poorer survival outcomes in pazopanib- or sunitinib-treated patients with aRCC. These findings provide insight in aRCC prognosis and may advance our thinking in development of new therapies.

Background: Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target., Methods: We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis., Findings: Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials)., Interpretation: The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition., Funding: The funding sources are cited at the end of the paper., (Copyright © 2015 Swerdlow et al. Open Access article distributed under the terms of CC BY. Published by Elsevier Ltd. All rights reserved.)

Background: Familial hypercholesterolemia (FH) is an autosomal-dominant disorder caused by mutations in 1 of 3 genes. In the 60% of patients who are mutation negative, we have recently shown that the clinical phenotype can be associated with an accumulation of common small-effect LDL cholesterol (LDL-C)-raising alleles by use of a 12-single nucleotide polymorphism (12-SNP) score. The aims of the study were to improve the selection of SNPs and replicate the results in additional samples., Methods: We used ROC curves to determine the optimum number of LDL-C SNPs. For replication analysis, we genotyped patients with a clinical diagnosis of FH from 6 countries for 6 LDL-C-associated alleles. We compared the weighted SNP score among patients with no confirmed mutation (FH/M-), those with a mutation (FH/M+), and controls from a UK population sample (WHII)., Results: Increasing the number of SNPs to 33 did not improve the ability of the score to discriminate between FH/M- and controls, whereas sequential removal of SNPs with smaller effects/lower frequency showed that a weighted score of 6 SNPs performed as well as the 12-SNP score. Metaanalysis of the weighted 6-SNP score, on the basis of polymorphisms in CELSR2 (cadherin, EGF LAG 7-pass G-type receptor 2), APOB (apolipoprotein B), ABCG5/8 [ATP-binding cassette, sub-family G (WHITE), member 5/8], LDLR (low density lipoprotein receptor), and APOE (apolipoprotein E) loci, in the independent FH/M- cohorts showed a consistently higher score in comparison to the WHII population (P < 2.2 × 10(-16)). Modeling in individuals with a 6-SNP score in the top three-fourths of the score distribution indicated a >95% likelihood of a polygenic explanation of their increased LDL-C., Conclusions: A 6-SNP LDL-C score consistently distinguishes FH/M- patients from healthy individuals. The hypercholesterolemia in 88% of mutation-negative patients is likely to have a polygenic basis., (© 2014 American Association for Clinical Chemistry.)

Background: Mendelian randomization studies have so far restricted attention to linear associations relating the genetic instrument to the exposure, and the exposure to the outcome. In some cases, however, observational data suggest a non-linear association between exposure and outcome. For example, alcohol consumption is consistently reported as having a U-shaped association with cardiovascular events. In principle, Mendelian randomization could address concerns that the apparent protective effect of light-to-moderate drinking might reflect 'sick-quitters' and confounding., Methods: The Alcohol-ADH1B Consortium was established to study the causal effects of alcohol consumption on cardiovascular events and biomarkers, using the single nucleotide polymorphism rs1229984 in ADH1B as a genetic instrument. To assess non-linear causal effects in this study, we propose a novel method based on estimating local average treatment effects for discrete levels of the exposure range, then testing for a linear trend in those effects. Our method requires an assumption that the instrument has the same effect on exposure in all individuals. We conduct simulations examining the robustness of the method to violations of this assumption, and apply the method to the Alcohol-ADH1B Consortium data., Results: Our method gave a conservative test for non-linearity under realistic violations of the key assumption. We found evidence for a non-linear causal effect of alcohol intake on several cardiovascular traits., Conclusions: We believe our method is useful for inferring departure from linearity when only a binary instrument is available. We estimated non-linear causal effects of alcohol intake which could not have been estimated through standard instrumental variable approaches., (© The Author 2014; Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Low plasma 25-hydroxyvitamin D (25[OH]D) concentration is associated with high arterial blood pressure and hypertension risk, but whether this association is causal is unknown. We used a mendelian randomisation approach to test whether 25(OH)D concentration is causally associated with blood pressure and hypertension risk., Methods: In this mendelian randomisation study, we generated an allele score (25[OH]D synthesis score) based on variants of genes that affect 25(OH)D synthesis or substrate availability (CYP2R1 and DHCR7), which we used as a proxy for 25(OH)D concentration. We meta-analysed data for up to 108 173 individuals from 35 studies in the D-CarDia collaboration to investigate associations between the allele score and blood pressure measurements. We complemented these analyses with previously published summary statistics from the International Consortium on Blood Pressure (ICBP), the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and the Global Blood Pressure Genetics (Global BPGen) consortium., Findings: In phenotypic analyses (up to n=49 363), increased 25(OH)D concentration was associated with decreased systolic blood pressure (β per 10% increase, -0·12 mm Hg, 95% CI -0·20 to -0·04; p=0·003) and reduced odds of hypertension (odds ratio [OR] 0·98, 95% CI 0·97-0·99; p=0·0003), but not with decreased diastolic blood pressure (β per 10% increase, -0·02 mm Hg, -0·08 to 0·03; p=0·37). In meta-analyses in which we combined data from D-CarDia and the ICBP (n=146 581, after exclusion of overlapping studies), each 25(OH)D-increasing allele of the synthesis score was associated with a change of -0·10 mm Hg in systolic blood pressure (-0·21 to -0·0001; p=0·0498) and a change of -0·08 mm Hg in diastolic blood pressure (-0·15 to -0·02; p=0·01). When D-CarDia and consortia data for hypertension were meta-analysed together (n=142 255), the synthesis score was associated with a reduced odds of hypertension (OR per allele, 0·98, 0·96-0·99; p=0·001). In instrumental variable analysis, each 10% increase in genetically instrumented 25(OH)D concentration was associated with a change of -0·29 mm Hg in diastolic blood pressure (-0·52 to -0·07; p=0·01), a change of -0·37 mm Hg in systolic blood pressure (-0·73 to 0·003; p=0·052), and an 8·1% decreased odds of hypertension (OR 0·92, 0·87-0·97; p=0·002)., Interpretation: Increased plasma concentrations of 25(OH)D might reduce the risk of hypertension. This finding warrants further investigation in an independent, similarly powered study., Funding: British Heart Foundation, UK Medical Research Council, and Academy of Finland., (Copyright © 2014 Vimaleswaran et al. Open Access article distributed under the terms of CC BY. Published by .. All rights reserved.)

Objective: Observational studies have examined the link between vitamin D deficiency and obesity traits. Some studies have reported associations between vitamin D pathway genes such as VDR, GC and CYP27B1 with body mass index (BMI) and waist circumference (WC); however, the findings have been inconsistent. Therefore, we investigated the involvement of vitamin D metabolic pathway genes in obesity-related traits in a large population-based study., Methods: We undertook a comprehensive analysis between 100 tagging single nucleotide polymorphisms (tagSNPs) in genes encoding for DHCR7, CYP2R1, VDBP, CYP27B1, CYP27A1, CYP24A1, VDR and RXRG, and obesity traits in 5224 participants (aged 45 years) in the 1958 British birth cohort (1958BC). We further extended our analyses to investigate the associations between SNPs and obesity traits using the summary statistics from the GIANT (Genetic Investigation of Anthropometric Traits) consortium (n=123 865)., Results: In the 1958BC (n=5224), after Bonferroni correction, none of the tagSNPs were associated with obesity traits except for one tagSNP from CYP24A1 that was associated with waist-hip ratio (WHR) (rs2296239, P=0.001). However, the CYP24A1 SNP was not associated with BMI-adjusted WHR (WHRadj) in the 1958BC (rs2296239, P=1.00) and GIANT results (n=123 865, P=0.18). There was also no evidence for an interaction between the tagSNPs and obesity on BMI, WC, WHR and WHRadj in the 1958BC. In the GIANT consortium, none of the tagSNPs were associated with obesity traits., Conclusions: Despite a very large study, our findings suggest that the vitamin D pathway genes are unlikely to have a major role in obesity-related traits in the general population.

Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies.

Objective: To investigate the impact on mortality due to pneumonia or influenza of the change from risk-based to age group-based targeting of the elderly for yearly influenza vaccination in England and Wales., Design: Excess mortality estimated using time series of deaths registered to pneumonia or influenza, accounting for seasonality, trend and artefacts. Non-excess mortality plotted as proxy for long-term trend in mortality., Setting: England and Wales., Participants: Persons aged 65-74 and 75+ years whose deaths were registered to underlying pneumonia or influenza between 1975/1976 and 2004/2005., Outcome Measures: Multiplicative effect on average excess pneumonia and influenza deaths each winter in the 4-6 winters since age group-based targeting of vaccination was introduced (in persons aged 75+ years from 1998/1999; in persons aged 65+ years from 2000/2001), estimated using multivariable regression adjusted for temperature, antigenic drift and vaccine mismatch, and stratified by dominant circulating influenza subtype. Trend in baseline weekly pneumonia and influenza death rates., Results: There is a suggestion of lower average excess mortality in the six winters after age group-based targeting began compared to before, but the CI for the 65-74 years age group includes no difference. Trend in baseline pneumonia and influenza mortality shows an apparent downward turning point around 2000 for the 65-74 years age group and from the mid-1990s in the 75+ years age group., Conclusions: There is weakly supportive evidence that the marked increases in vaccine coverage accompanying the switch from risk-based to age group-based targeting of the elderly for yearly influenza vaccination in England and Wales were associated with lower levels of pneumonia and influenza mortality in older people in the first 6 years after age group-based targeting began. The possible impact of these policy changes is observed as weak evidence for lower average excess mortality as well as a turning point in baseline mortality coincident with the changes.

Clinical trials for preventative therapies are complex and costly endeavors focused on individuals likely to develop disease in a short time frame, randomizing them to treatment groups, and following them over time. In such trials, statistical power is governed by the rate of disease events in each group and cost is determined by randomization, treatment, and follow-up. Strategies that increase the rate of disease events by enrolling individuals with high risk of disease can significantly reduce study size, duration, and cost. Comprehensive study of common, complex diseases has resulted in a growing list of robustly associated genetic markers. Here, we evaluate the utility--in terms of trial size, duration, and cost--of enriching prevention trial samples by combining clinical information with genetic risk scores to identify individuals at greater risk of disease. We also describe a framework for utilizing genetic risk scores in these trials and evaluating the associated cost and time savings. With type 1 diabetes (T1D), type 2 diabetes (T2D), myocardial infarction (MI), and advanced age-related macular degeneration (AMD) as examples, we illustrate the potential and limitations of using genetic data for prevention trial design. We illustrate settings where incorporating genetic information could reduce trial cost or duration considerably, as well as settings where potential savings are negligible. Results are strongly dependent on the genetic architecture of the disease, but we also show that these benefits should increase as the list of robustly associated markers for each disease grows and as large samples of genotyped individuals become available., (Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Objectives: This study sought to ascertain the relationship of 9p21 locus with: 1) angiographic coronary artery disease (CAD) burden; and 2) myocardial infarction (MI) in individuals with underlying CAD., Background: Chromosome 9p21 variants have been robustly associated with coronary heart disease, but questions remain on the mechanism of risk, specifically whether the locus contributes to coronary atheroma burden or plaque instability., Methods: We established a collaboration of 21 studies consisting of 33,673 subjects with information on both CAD (clinical or angiographic) and MI status along with 9p21 genotype. Tabular data are provided for each cohort on the presence and burden of angiographic CAD, MI cases with underlying CAD, and the diabetic status of all subjects., Results: We first confirmed an association between 9p21 and CAD with angiographically defined cases and control subjects (pooled odds ratio [OR]: 1.31, 95% confidence interval [CI]: 1.20 to 1.43). Among subjects with angiographic CAD (n = 20,987), random-effects model identified an association with multivessel CAD, compared with those with single-vessel disease (OR: 1.10, 95% CI: 1.04 to 1.17)/copy of risk allele). Genotypic models showed an OR of 1.15, 95% CI: 1.04 to 1.26 for heterozygous carrier and OR: 1.23, 95% CI: 1.08 to 1.39 for homozygous carrier. Finally, there was no significant association between 9p21 and prevalent MI when both cases (n = 17,791) and control subjects (n = 15,882) had underlying CAD (OR: 0.99, 95% CI: 0.95 to 1.03)/risk allele., Conclusions: The 9p21 locus shows convincing association with greater burden of CAD but not with MI in the presence of underlying CAD. This adds further weight to the hypothesis that 9p21 locus primarily mediates an atherosclerotic phenotype., (Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Background: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis., Methods and Findings: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m(2) higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10⁻²⁷). The BMI allele score was associated both with BMI (p = 6.30×10⁻⁶²) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10⁻⁵⁷ for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores)., Conclusions: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

Background: Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk., Objective: To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa., Design, Setting, and Participants: Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated., Outcome Measurements and Statistical Analysis: Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers., Results and Limitations: Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10(-8)). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p<0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p=0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥ 7) PCa. A major limitation of this study was its focus on white patients only., Conclusions: Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study., (Copyright © 2012 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

There are many known examples of multiple semi-independent associations at individual loci; such associations might arise either because of true allelic heterogeneity or because of imperfect tagging of an unobserved causal variant. This phenomenon is of great importance in monogenic traits but has not yet been systematically investigated and quantified in complex-trait genome-wide association studies (GWASs). Here, we describe a multi-SNP association method that estimates the effect of loci harboring multiple association signals by using GWAS summary statistics. Applying the method to a large anthropometric GWAS meta-analysis (from the Genetic Investigation of Anthropometric Traits consortium study), we show that for height, body mass index (BMI), and waist-to-hip ratio (WHR), 3%, 2%, and 1%, respectively, of additional phenotypic variance can be explained on top of the previously reported 10% (height), 1.5% (BMI), and 1% (WHR). The method also permitted a substantial increase (by up to 50%) in the number of loci that replicate in a discovery-validation design. Specifically, we identified 74 loci at which the multi-SNP, a linear combination of SNPs, explains significantly more variance than does the best individual SNP. A detailed analysis of multi-SNPs shows that most of the additional variability explained is derived from SNPs that are not in linkage disequilibrium with the lead SNP, suggesting a major contribution of allelic heterogeneity to the missing heritability., (Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids., (Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Elevated plasma levels of lipoprotein-associated phospholipase A(2) (Lp-PLA2) activity have been shown to be associated with increased risk of coronary heart disease and an inhibitor of this enzyme is under development for the treatment of that condition. A Val279Phe null allele in this gene, that may influence patient eligibility for treatment, is relatively common in East Asians but has not been observed in Europeans. We investigated the existence and functional effects of low frequency alleles in a Western European population by re-sequencing the exons of PLA2G7 in 2000 samples. In all, 19 non-synonymous single-nucleotide polymorphisms (nsSNPs) were found, 14 in fewer than four subjects (minor allele frequency <0.1%). Lp-PLA2 activity was significantly lower in rare nsSNP carriers compared with non-carriers (167.8±63.2 vs 204.6±41.8, P=0.01) and seven variants had enzyme activities consistent with a null allele. The cumulative frequency of these null alleles was 0.25%, so <1 in 10,000 Europeans would be expected to be homozygous, and thus not potentially benefit from treatment with an Lp-PLA2 inhibitor.