Associations of adolescents' diet and meal patterns with school performance in the Northern Finland Birth Cohort 1986: A Mendelian randomisation study.

BACKGROUND: Several observational studies indicate that dietary habits in children and adolescents are associated with school performance. These associations are heavily confounded by socio-economic characteristics, such as household income and parents' educational attainment, amongst other factors. The objective of this study was to explore the association between diet and school performance in adolescents from the Northern Finland Birth Cohort 1986 (NFBC1986). METHODS: Dietary and school performance data were collected using self-reported questionnaires from adolescents in the NFBC1986 cross-sectional, 16-year follow-up study. In this work we derived exploratory factors for the dietary variables, frequency of skipping main meals and school performance variables, performed genome-wide association studies (GWAS) against these factors to obtain genetic association data and conducted one-sample and two-sample Mendelian randomisation (MR) analyses using individual level data for up to 9220 adolescents in NFBC1986 and GWAS results from external cohorts. We report observational and MR effects of diet on school performance and cognition-related phenotypes. RESULTS: The observational study and the one-sample Mendelian randomisation analysis showed that high fat, salt and sugar (HFSS) consumption was associated with poor school performance in general/science subjects (-0.080, -0.128 to -0.033) and staple food consumption with better school performance in general/science subjects (0.071, 0.024 to 0.119) and physical education (0.065, 0.021 to 0.110). Findings from our two-sample MR analysis identified dietary principal components described best as whole brain bread, wheat, cheese, oat cereal and red wine to be associated with higher educational attainment and other cognition-related phenotypes. CONCLUSION: Using genetics, we highlighted the potential role of HFSS food consumption and consumption of the components of a staple food diet for school performance. However, further research is required to find conclusive evidence that could support a causal role of diet on school performance.

Associations of genetically predicted fatty acid levels across the phenome: A mendelian randomisation study.

BACKGROUND: Fatty acids are important dietary factors that have been extensively studied for their implication in health and disease. Evidence from epidemiological studies and randomised controlled trials on their role in cardiovascular, inflammatory, and other diseases remains inconsistent. The objective of this study was to assess whether genetically predicted fatty acid concentrations affect the risk of disease across a wide variety of clinical health outcomes. METHODS AND FINDINGS: The UK Biobank (UKB) is a large study involving over 500,000 participants aged 40 to 69 years at recruitment from 2006 to 2010. We used summary-level data for 117,143 UKB samples (base dataset), to extract genetic associations of fatty acids, and individual-level data for 322,232 UKB participants (target dataset) to conduct our discovery analysis. We studied potentially causal relationships of circulating fatty acids with 845 clinical diagnoses, using mendelian randomisation (MR) approach, within a phenome-wide association study (PheWAS) framework. Regression models in PheWAS were adjusted for sex, age, and the first 10 genetic principal components. External summary statistics were used for replication. When several fatty acids were associated with a health outcome, multivariable MR and MR-Bayesian method averaging (MR-BMA) was applied to disentangle their causal role. Genetic predisposition to higher docosahexaenoic acid (DHA) was associated with cholelithiasis and cholecystitis (odds ratio per mmol/L: 0.76, 95% confidence interval: 0.66 to 0.87). This was supported in replication analysis (FinnGen study) and by the genetically predicted omega-3 fatty acids analyses. Genetically predicted linoleic acid (LA), omega-6, polyunsaturated fatty acids (PUFAs), and total fatty acids (total FAs) showed positive associations with cardiovascular outcomes with support from replication analysis. Finally, higher genetically predicted levels of DHA (0.83, 0.73 to 0.95) and omega-3 (0.83, 0.75 to 0.92) were found to have a protective effect on obesity, which was supported using body mass index (BMI) in the GIANT consortium as replication analysis. Multivariable MR analysis suggested a direct detrimental effect of LA (1.64, 1.07 to 2.50) and omega-6 fatty acids (1.81, 1.06 to 3.09) on coronary heart disease (CHD). MR-BMA prioritised LA and omega-6 fatty acids as the top risk factors for CHD. Although we present a range of sensitivity analyses to the address MR assumptions, horizontal pleiotropy may still bias the reported associations and further evaluation in clinical trials is needed. CONCLUSIONS: Our study suggests potentially protective effects of circulating DHA and omega-3 concentrations on cholelithiasis and cholecystitis and on obesity, highlighting the need to further assess them as prevention treatments in clinical trials. Moreover, our findings do not support the supplementation of unsaturated fatty acids for cardiovascular disease prevention.

Systems epidemiology of metabolomics measures reveals new relationships between lipoproteins and other small molecules.

INTRODUCTION: The study of lipoprotein metabolism at the population level can provide valuable information for the organisation of lipoprotein related processes in the body. To use this information towards interventional hypotheses generation and testing, we need to be able to identify the mechanistic connections among the large number of observed correlations between the measured components of the system. OBJECTIVES: To use population level metabolomics information to gain insight on their biochemical networks and metabolism. METHODS: Genetic and metabolomics information for 230 metabolic measures, predominately lipoprotein related, from a targeted nuclear magnetic resonance approach, in two samples of an established European cohort, totalling more than 9400 individuals analysed using phenotypic and genetic correlations, as well as Mendelian Randomisation. RESULTS: More than 20,500 phenotypic correlations were identified in the data, with almost 2000 also showing evidence of strong genetic correlation. Mendelian randomisation, provided evidence for a causal effect between 9496 pairs of metabolic measures, mainly between lipoprotein traits. The results provide insights on the organisation of lipoproteins in three distinct classes, the heterogeneity between HDL particles, and the association, or lack of, between CLA, glycolysis markers, such as glucose and citrate, and glycoproteins with lipids subfractions. Two examples for the use of the approach in systems biology of lipoproteins are presented. CONCLUSIONS: Genetic variation can be used to infer the underlying mechanisms for the associations between lipoproteins for hypothesis generation and confirmation, and, together with biological information, to map complex biological processes.

Polycystic ovary syndrome (PCOS) and COVID-19: an overlooked female patient population at potentially higher risk during the COVID-19 pandemic.

BACKGROUND: In women of reproductive age, polycystic ovary syndrome (PCOS) constitutes the most frequent endocrine disorder. Women with PCOS are considered to typically belong to an age and sex group which is at lower risk for severe COVID-19. MAIN BODY: Emerging data link the risk of severe COVID-19 with certain factors such as hyper-inflammation, ethnicity predisposition, low vitamin D levels, and hyperandrogenism, all of which have known direct associations with PCOS. Moreover, in this common female patient population, there is markedly high prevalence of multiple cardio-metabolic conditions, such as type 2 diabetes, obesity, and hypertension, which may significantly increase the risk for adverse COVID-19-related outcomes. This strong overlap of risk factors for both worse PCOS cardio-metabolic manifestations and severe COVID-19 should be highlighted for the clinical practice, particularly since women with PCOS often receive fragmented care from multiple healthcare services. Comprehensively informing women with PCOS regarding the potential risks from COVID-19 and how this may affect their management is also essential. CONCLUSION: Despite the immense challenges posed by the COVID-19 outbreak to the healthcare systems in affected countries, attention should be directed to maintain a high standard of care for complex patients such as many women with PCOS and provide relevant practical recommendations for optimal management in the setting of this fast moving pandemic.

Mechanistic insights from combining genomics with metabolomics.

PURPOSE OF REVIEW: Metabolomics directly measure substrates and products of biological processes and pathways. Based on instrumentation and throughput advances, the use of metabolomics has only recently become feasible at the population level. This has led to an intense interest in using the new information in combination with genomics, and other omics technologies, to give biological context to the rapidly accumulating associations between genes and diseases or their risk factors. RECENT FINDINGS: The use of metabolomics-genomic associations for the metabolic characterization of genes of interest has confirmed known pathways and permitted the identification of new ones. These include the unknown metabolite X12063 linking statins to myopathies, the role of glycerophospholipids in cholesterol metabolism, the structure of lipoprotein (a), the lipoprotein lipase-independent effect of Apolipoprotein C-III coding and the role of branched chain amino acids in the antagonistic coregulation of levels of HDLs and triglyceride. SUMMARY: The findings reviewed illustrate the importance of integrating metabolomics and genomics for the greater understanding of biological mechanisms. The limitations of the current approaches are also discussed together with approaches that will be required to make the most of the current multiomics data available.

Identifying gene-gene interactions that are highly associated with four quantitative lipid traits across multiple cohorts.

Genetic loci explain only 25-30 % of the heritability observed in plasma lipid traits. Epistasis, or gene-gene interactions may contribute to a portion of this missing heritability. Using the genetic data from five NHLBI cohorts of 24,837 individuals, we combined the use of the quantitative multifactor dimensionality reduction (QMDR) algorithm with two SNP-filtering methods to exhaustively search for SNP-SNP interactions that are associated with HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), total cholesterol (TC) and triglycerides (TG). SNPs were filtered either on the strength of their independent effects (main effect filter) or the prior knowledge supporting a given interaction (Biofilter). After the main effect filter, QMDR identified 20 SNP-SNP models associated with HDL-C, 6 associated with LDL-C, 3 associated with TC, and 10 associated with TG (permutation P value <0.05). With the use of Biofilter, we identified 2 SNP-SNP models associated with HDL-C, 3 associated with LDL-C, 1 associated with TC and 8 associated with TG (permutation P value <0.05). In an independent dataset of 7502 individuals from the eMERGE network, we replicated 14 of the interactions identified after main effect filtering: 11 for HDL-C, 1 for LDL-C and 2 for TG. We also replicated 23 of the interactions found to be associated with TG after applying Biofilter. Prior knowledge supports the possible role of these interactions in the genetic etiology of lipid traits. This study also presents a computationally efficient pipeline for analyzing data from large genotyping arrays and detecting SNP-SNP interactions that are not primarily driven by strong main effects.

Assessment of the clinical utility of adding common single nucleotide polymorphism genetic scores to classical risk factor algorithms in coronary heart disease risk prediction in UK men.

BACKGROUND: Risk prediction algorithms for coronary heart disease (CHD) are recommended for clinical use. However, their predictive ability remains modest and the inclusion of genetic risk may improve their performance. METHODS: QRISK2 was used to assess CHD risk using conventional risk factors (CRFs). The performance of a 19 single nucleotide polymorphism (SNP) gene score (GS) for CHD including variants identified by genome-wide association study and candidate gene studies (weighted using the results from the CARDIoGRAMplusC4D meta-analysis) was assessed using the second Northwick Park Heart Study (NPHSII) of 2775 healthy UK men (284 cases). To improve the GS, five SNPs with weak evidence of an association with CHD were removed and replaced with seven robustly associated SNPs - giving a 21-SNP GS. RESULTS: The weighted 19 SNP GS was associated with lipid traits (p<0.05) and CHD after adjustment for CRFs, (OR=1.31 per standard deviation, p=0.03). Addition of the 19 SNP GS to QRISK2 showed improved discrimination (area under the receiver operator characteristic curve 0.68 vs. 0.70 p=0.02), a positive net reclassification index (0.07, p=0.04) compared to QRISK2 alone and maintained good calibration (p=0.17). The 21-SNP GS was also associated with CHD after adjustment for CRFs (OR=1.39 per standard deviation, 1.42×10-3), but the combined QRISK2 plus GS score was poorly calibrated (p=0.03) and showed no improvement in discrimination (p=0.55) or reclassification (p=0.10) compared to QRISK2 alone. CONCLUSIONS: The 19-SNP GS is robustly associated with CHD and showed potential clinical utility in the UK population.

HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials.

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.

Variant rs10911021 that associates with coronary heart disease in type 2 diabetes, is associated with lower concentrations of circulating HDL cholesterol and large HDL particles but not with amino acids.

AIMS: An intergenic locus on chromosome 1 (lead SNP rs10911021) was previously associated with coronary heart disease (CHD) in type 2 diabetes (T2D). Using data from the UCLEB consortium we investigated the relationship between rs10911021 and CHD in T2D, whether rs10911021 was associated with levels of amino acids involved in the γ-glutamyl cycle or any conventional risk factors (CRFs) for CHD in the T2D participants. METHODS: Four UCLEB studies (n = 6531) had rs10911021 imputation, CHD in T2D, CRF and metabolomics data determined using a nuclear magnetic resonance based platform. RESULTS: The expected direction of effect between rs10911021 and CHD in T2D was observed (1377 no CHD/160 CHD; minor allele OR 0.80, 95 % CI 0.60-1.06) although this was not statistically significant (p = 0.13). No association between rs10911021 and CHD was seen in non-T2D participants (11218 no CHD/1274 CHD; minor allele OR 1.00 95 % CIs 0.92-1.10). In T2D participants, while no associations were observed between rs10911021 and the nine amino acids measured, rs10911021 was associated with HDL-cholesterol (p = 0.0005) but the minor "protective" allele was associated with lower levels (-0.034 mmol/l per allele). Focusing more closely on the HDL-cholesterol subclasses measured, we observed that rs10911021 was associated with six large HDL particle measures in T2D (all p < 0.001). No significant associations were seen in non-T2D subjects. CONCLUSIONS: Our findings are consistent with a true association between rs10911021 and CHD in T2D. The protective minor allele was associated with lower HDL-cholesterol and reductions in HDL particle traits. Our results indicate a complex relationship between rs10911021 and CHD in T2D.

Mendelian randomization of blood lipids for coronary heart disease.

AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

Genetic meta-analysis of 15,901 African Americans identifies variation in EXOC3L1 is associated with HDL concentration.

Meta-analyses of European populations has successfully identified genetic variants in over 150 loci associated with lipid levels, but results from additional ethnicities remain limited. Previously, we reported two novel lipid loci identified in a sample of 7,657 African Americans using a gene-centric array including 50,000 SNPs in 2,100 candidate genes. Initial discovery and follow-up of signals with P < 10(-5) in additional African American samples confirmed CD36 and ICAM1. Using an additional 8,244 African American female samples from the Women's Health Initiative SNP Health Association Resource genome-wide association study dataset, we further examined the previous meta-analyses results by attempting to replicate 20 additional putative lipid signals with P < 10(-4). Replication confirmed rs868213, located in a splice donor region of exocyst complex component 3-like 1 (EXOC3L1) as a novel signal for HDL (additive allelic effect ß = 0.02; P = 1.4 × 10(-8); meta-analyses of discovery and replication). EXOC3L1 is strongly expressed in vascular endothelium and forms part of the exocyst complex, a key facilitator of the trafficking of lipid receptors. Increasing sample sizes for genetic studies in nonEuropean populations will continue to improve our understanding of lipid metabolism.

Large-scale gene-centric meta-analysis across 39 studies identifies type 2 diabetes loci.

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with ∼2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 × 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p < 2.4 × 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 × 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 × 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 × 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups.

Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study.

BACKGROUND: Familial hypercholesterolaemia is a common autosomal-dominant disorder caused by mutations in three known genes. DNA-based cascade testing is recommended by UK guidelines to identify affected relatives; however, about 60% of patients are mutation-negative. We assessed the hypothesis that familial hypercholesterolaemia can also be caused by an accumulation of common small-effect LDL-C-raising alleles. METHODS: In November, 2011, we assembled a sample of patients with familial hypercholesterolaemia from three UK-based sources and compared them with a healthy control sample from the UK Whitehall II (WHII) study. We also studied patients from a Belgian lipid clinic (Hôpital de Jolimont, Haine St-Paul, Belgium) for validation analyses. We genotyped participants for 12 common LDL-C-raising alleles identified by the Global Lipid Genetics Consortium and constructed a weighted LDL-C-raising gene score. We compared the gene score distribution among patients with familial hypercholesterolaemia with no confirmed mutation, those with an identified mutation, and controls from WHII. FINDINGS: We recruited 321 mutation-negative UK patients (451 Belgian), 319 mutation-positive UK patients (273 Belgian), and 3020 controls from WHII. The mean weighted LDL-C gene score of the WHII participants (0.90 [SD 0.23]) was strongly associated with LDL-C concentration (p=1.4 x 10(-77); R(2)=0.11). Mutation-negative UK patients had a significantly higher mean weighted LDL-C score (1.0 [SD 0.21]) than did WHII controls (p=4.5 x 10(-16)), as did the mutation-negative Belgian patients (0.99 [0.19]; p=5.2 x 10(-20)). The score was also higher in UK (0.95 [0.20]; p=1.6 x 10(-5)) and Belgian (0.92 [0.20]; p=0.04) mutation-positive patients than in WHII controls. 167 (52%) of 321 mutation-negative UK patients had a score within the top three deciles of the WHII weighted LDL-C gene score distribution, and only 35 (11%) fell within the lowest three deciles. INTERPRETATION: In a substantial proportion of patients with familial hypercholesterolaemia without a known mutation, their raised LDL-C concentrations might have a polygenic cause, which could compromise the efficiency of cascade testing. In patients with a detected mutation, a substantial polygenic contribution might add to the variable penetrance of the disease. FUNDING: British Heart Foundation, Pfizer, AstraZeneca, Schering-Plough, National Institute for Health Research, Medical Research Council, Health and Safety Executive, Department of Health, National Heart Lung and Blood Institute, National Institute on Aging, Agency for Health Care Policy Research, John D and Catherine T MacArthur Foundation Research Networks on Successful Midlife Development and Socio-economic Status and Health, Unilever, and Departments of Health and Trade and Industry.

The use of haplotypes in the identification of interaction between SNPs.

Although haplotypes can provide great insight into the complex relationships between functional polymorphisms at a locus, their use in modern association studies has been limited. This is due to our inability to directly observe haplotypes in studies of unrelated individuals, but also to the extra complexity involved in their analysis and the difficulty in identifying which is the truly informative haplotype. Using a series of simulations, we tested a number of different models of a haplotype carrying two functional single nucleotide polymorphisms (SNPs) to assess the ability of haplotypic analysis to identify functional interactions between SNPs at the same locus. We found that, when phase is known, analysis of the haplotype is more powerful than analysis of the individual SNPs. The difference between the two approaches becomes less either as an increasing number of non-informative SNPs are included, or when the haplotypic phase is unknown, while in both cases the SNP association becomes progressively better at identifying the association. Our results suggest that when novel genotyping and bioinformatics methods are available to reconstruct haplotypic phase, this will permit the emergence of a new wave of haplotypic analysis able to consider interactions between SNPs with increased statistical power.

Influence of common genetic variation on blood lipid levels, cardiovascular risk, and coronary events in two British prospective cohort studies.

AIMS: The aim of this study was to quantify the collective effect of common lipid-associated single nucleotide polymorphisms (SNPs) on blood lipid levels, cardiovascular risk, use of lipid-lowering medication, and risk of coronary heart disease (CHD) events. METHODS AND RESULTS: Analysis was performed in two prospective cohorts: Whitehall II (WHII; N = 5059) and the British Women's Heart and Health Study (BWHHS; N = 3414). For each participant, scores were calculated based on the cumulative effect of multiple genetic variants influencing total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Compared with the bottom quintile, individuals in the top quintile of the LDL-C genetic score distribution had higher LDL-C {mean difference of 0.85 [95% confidence interval, (CI) = 0.76-0.94] and 0.63 [95% CI = 0.50-0.76] mmol/l in WHII and BWHHS, respectively}. They also tended to have greater odds of having 'high-risk' status (Framingham 10-year cardiovascular disease risk >20%) [WHII: odds ratio (OR) = 1.36 (0.93-1.98), BWHHS: OR = 1.49 (1.14-1.94)]; receiving lipid-lowering treatment [WHII: OR = 2.38 (1.57-3.59), BWHHS: OR = 2.24 (1.52-3.29)]; and CHD events [WHII: OR = 1.43 (1.02-2.00), BWHHS: OR = 1.31 (0.99-1.72)]. Similar associations were observed for the TC score in both studies. The TG score was associated with high-risk status and medication use in both studies. Neither HDL nor TG scores were associated with the risk of coronary events. The genetic scores did not improve discrimination over the Framingham risk score. CONCLUSION: At the population level, common SNPs associated with LDL-C and TC contribute to blood lipid variation, cardiovascular risk, use of lipid-lowering medications and coronary events. However, their effects are too small to discriminate future lipid-lowering medication requirements or coronary events.

Progress in genetic association studies of plasma lipids.

PURPOSE OF REVIEW: This review summarizes recently published large-scale efforts elucidating the genetic architecture of lipid levels. A supplemental file with all genetic loci is provided for research purposes and we performed bioinformatic analyses of the genetic variants to give an oversight of involved pathways. RECENT FINDINGS: In total, 52 genes for HDL cholesterol, 42 genes for LDL cholesterol, 59 genes for total cholesterol, and 39 genes for triglycerides have been identified. Genetic overlap is present between the different traits and similar pathways are involved. Most of the SNPs that were detected in the European studies could be replicated in other ethnicities and these SNPs show the same direction of effect suggesting that the underlying genetic architecture of blood lipids is similar between ethnicities. SUMMARY: Genetic studies have identified many loci associated with plasma lipids and have provided insight into the underlying mechanisms of lipid homeostasis. Future research is needed to determine whether these loci may be novel targets for lipid-lowering therapy and for reducing cardiovascular disease risk. In addition, the proportion of genetic variance explained by these lipid loci is still limited and new large-scale genetic studies are ongoing to identify additional common and rare variants associated with lipid levels.

Using genetics to investigate the association between lanosterol and cataract.

Background: Cataract is one of the most prevalent causes of blindness worldwide. Whilst surgery is the primary treatment for cataracts, it is not always an available option, particularly in developing countries. Non-surgical methods of treatment would increase treatment availability for more patients. Several studies have investigated how topical application of oxysterols, such as lanosterol, may break down aggregated proteins and restore lens transparency. However, the results are conflicting and inconclusive. Aim: In this study, we focus on combining genetic evidence for associations between lanosterol related genetic variation and cataract to explore whether lanosterol is a potentially suitable drug treatment option. Method: Using data from 45,449 available cataract cases from the UK Biobank, with participant ages ranging from 40-69, we conducted a genetic association study (GWAS) to assess the risk of cataract. Cataract cases were defined using diagnostic and operation codes. We focused on genetic variants in the lanosterol synthase gene region. We also compared our results with previously published genetic associations of phytosterol-to-lanosterol ratios. Finally, we performed a genetic risk score analysis to test the association between lanosterol within the cholesterol synthesis pathway and the risk of cataract. Results: No statistically significant single nucleotide polymorphisms (SNPs) associations with cataract were observed in the gene region of lanosterol synthase at a multiple testing adjusted significance threshold of p < 0.05/13. The comparison between cataract risk and genetic association of 8 phytosterol-to-lanosterol GWAS results also showed no evidence to support lanosterol's protective properties for cataract risk. No statistically significant association was found between the lanosterol within the cholesterol synthesis pathway genetic risk score and cataract outcomes (OR = 1.002 p = 0.568). Conclusion: There was no evidence observed for genetic associations between lanosterol and cataract risk. Our results do not support lanosterol's potential role in treating cataracts. Further research may be needed to address the effect of lanosterol on specific cataract subtypes.

Exploring the contribution of lifestyle to the impact of education on the risk of cancer through Mendelian randomization analysis.

Educational attainment (EA) has been linked to the risk of several types of cancer, despite having no expected direct biological connection. In this paper, we investigate the mediating role of alcohol consumption, smoking, vegetable consumption, fruit consumption and body mass index (BMI) in explaining the effect of EA on 7 cancer groupings. Large-scale genome wide association study (GWAS) results were used to construct the genetic instrument for EA and the lifestyle factors. We conducted GWAS in the UK Biobank sample in up to 335,024 individuals to obtain genetic association data for the cancer outcomes. Univariable and multivariable two-sample Mendelian randomization (MR) analyses and mediation analyses were then conducted to explore the causal effect and mediating proportions of these relations. MR mediation analysis revealed that reduced lifetime smoking index accounted for 81.7% (49.1% to 100%) of the protective effect of higher EA on lower respiratory cancer. Moreover, the effect of higher EA on lower respiratory cancer was mediated through vegetable consumption by 10.2% (4.4% to 15.9%). We found genetic evidence that the effect of EA on groups of cancer is due to behavioural changes in avoiding well established risk factors such as smoking and vegetable consuming.

A systematic review of human evidence for the intergenerational effects of exposure to ionizing radiation.

PURPOSE: To provide a synthesis of the published evidence pertaining to the intergenerational health effects of parental preconceptional exposure to ionizing radiation in humans. METHODS: The study populations are the descendants of those who were exposed to ionizing radiation prior to conception. A Boolean search identified publications for review in accordance with Office of Health Assessment and Translation guidelines. Initially, a risk of bias assessment was conducted for each published study and relevant data extracted. Information was organized into adverse health outcome groups and exposure situations. To make an assessment from the body of evidence within each group, an initial confidence rating was assigned, before factors including inconsistencies between studies, magnitude of effect, dose response and confounders were considered. From this, 'an effect', 'no effect' or whether the evidence remained 'inadequate' to determine either effect or no effect, was ascertained. This assessment was based primarily upon the author's conclusions within that evidence-base and, by binomial probability testing of the direction of effect reported. RESULTS: 2441 publications were identified for review which after screening was reduced to 127. For the majority of the adverse health groups, we find there to be inadequate evidence from which to determine whether the health effect was, or was not, associated with parental preconceptional radiation exposure. This was largely due to heterogeneity between individual study's findings and conclusions within each group and, the limited number of studies within each group. We did observe one health grouping (congenital abnormalities) in occupationally exposed populations, where an increase in effect relative to their controls or large magnitude of effects, were reported, although it is noted that the authors of these studies interpreted their findings as most likely not to be associated with parental radiation exposure. CONCLUSIONS: We find there to be a lack of evidence to enable the formal assessment of radiation-related adverse effects in offspring of exposed humans. This is not the same as there being no clear evidence that effects may occur but does infer that if adverse health effects do arise in children of exposed parents, then these effects are small and difficult to reproducibly measure. Inconsistencies in designing studies are unavoidable, however we highlight the need for an element of standardization and, more sharing of primary datasets as part of open access initiatives, in order for future reviews to make reasonable conclusions. Overall, there is a need for future work to ensure comparable measures between studies where possible.

The interleukin-6 receptor as a target for prevention of coronary heart disease: a mendelian randomisation analysis.

BACKGROUND: A high circulating concentration of interleukin 6 is associated with increased risk of coronary heart disease. Blockade of the interleukin-6 receptor (IL6R) with a monoclonal antibody (tocilizumab) licensed for treatment of rheumatoid arthritis reduces systemic and articular inflammation. However, whether IL6R blockade also reduces risk of coronary heart disease is unknown. METHODS: Applying the mendelian randomisation principle, we used single nucleotide polymorphisms (SNPs) in the gene IL6R to evaluate the likely efficacy and safety of IL6R inhibition for primary prevention of coronary heart disease. We compared genetic findings with the effects of tocilizumab reported in randomised trials in patients with rheumatoid arthritis. FINDINGS: In 40 studies including up to 133,449 individuals, an IL6R SNP (rs7529229) marking a non-synonymous IL6R variant (rs8192284; p.Asp358Ala) was associated with increased circulating log interleukin-6 concentration (increase per allele 9·45%, 95% CI 8·34-10·57) as well as reduced C-reactive protein (decrease per allele 8·35%, 95% CI 7·31-9·38) and fibrinogen concentrations (decrease per allele 0·85%, 95% CI 0·60-1·10). This pattern of effects was consistent with IL6R blockade from infusions of tocilizumab (4-8 mg/kg every 4 weeks) in patients with rheumatoid arthritis studied in randomised trials. In 25,458 coronary heart disease cases and 100,740 controls, the IL6R rs7529229 SNP was associated with a decreased odds of coronary heart disease events (per allele odds ratio 0·95, 95% CI 0·93-0·97, p=1·53×10(-5)). INTERPRETATION: On the basis of genetic evidence in human beings, IL6R signalling seems to have a causal role in development of coronary heart disease. IL6R blockade could provide a novel therapeutic approach to prevention of coronary heart disease that warrants testing in suitably powered randomised trials. Genetic studies in populations could be used more widely to help to validate and prioritise novel drug targets or to repurpose existing agents and targets for new therapeutic uses. FUNDING: UK Medical Research Council; British Heart Foundation; Rosetrees Trust; US National Heart, Lung, and Blood Institute; Du Pont Pharma; Chest, Heart and Stroke Scotland; Wellcome Trust; Coronary Thrombosis Trust; Northwick Park Institute for Medical Research; UCLH/UCL Comprehensive Medical Research Centre; US National Institute on Aging; Academy of Finland; Netherlands Organisation for Health Research and Development; SANCO; Dutch Ministry of Public Health, Welfare and Sports; World Cancer Research Fund; Agentschap NL; European Commission; Swedish Heart-Lung Foundation; Swedish Research Council; Strategic Cardiovascular Programme of the Karolinska Institutet; Stockholm County Council; US National Institute of Neurological Disorders and Stroke; MedStar Health Research Institute; GlaxoSmithKline; Dutch Kidney Foundation; US National Institutes of Health; Netherlands Interuniversity Cardiology Institute of the Netherlands; Diabetes UK; European Union Seventh Framework Programme; National Institute for Healthy Ageing; Cancer Research UK; MacArthur Foundation.