Summary Background The metabolic effects of omega-6 polyunsaturated fatty acids (PUFAs) remain contentious, and little evidence is available regarding their potential role in primary prevention of type 2 diabetes. We aimed to assess the associations of linoleic acid and arachidonic acid biomarkers with incident type 2 diabetes. Methods We did a pooled analysis of new, harmonised, individual-level analyses for the biomarkers linoleic acid and its metabolite arachidonic acid and incident type 2 diabetes. We analysed data from 20 prospective cohort studies from ten countries (Iceland, the Netherlands, the USA, Taiwan, the UK, Germany, Finland, Australia, Sweden, and France), with biomarkers sampled between 1970 and 2010. Participants included in the analyses were aged 18 years or older and had data available for linoleic acid and arachidonic acid biomarkers at baseline. We excluded participants with type 2 diabetes at baseline. The main outcome was the association between omega-6 PUFA biomarkers and incident type 2 diabetes. We assessed the relative risk of type 2 diabetes prospectively for each cohort and lipid compartment separately using a prespecified analytic plan for exposures, covariates, effect modifiers, and analysis, and the findings were then pooled using inverse-variance weighted meta-analysis. Findings Participants were 39 740 adults, aged (range of cohort means) 49–76 years with a BMI (range of cohort means) of 23∙3–28∙4 kg/m2, who did not have type 2 diabetes at baseline. During a follow-up of 366 073 person-years, we identified 4347 cases of incident type 2 diabetes. In multivariable-adjusted pooled analyses, higher proportions of linoleic acid biomarkers as percentages of total fatty acid were associated with a lower risk of type 2 diabetes overall (risk ratio [RR] per interquintile range 0∙65, 95% CI 0∙60–0∙72, p<0·0001; I2=53·9%, pheterogeneity=0·002). The associations between linoleic acid biomarkers and type 2 diabetes were generally similar in different lipid compartments, including phospholipids, plasma, cholesterol esters, and adipose tissue. Levels of arachidonic acid biomarker were not significantly associated with type 2 diabetes risk overall (RR per interquintile range 0∙96, 95% CI 0∙88–1∙05; p=0∙38; I2=63·0%, pheterogeneity<0·0001). The associations between linoleic acid and arachidonic acid biomarkers and the risk of type 2 diabetes were not significantly modified by any prespecified potential sources of heterogeneity (ie, age, BMI, sex, race, aspirin use, omega-3 PUFA levels, or variants of the FADS gene; all pheterogeneity≥0∙13). Interpretation Findings suggest that linoleic acid has long-term benefits for the prevention of type 2 diabetes and that arachidonic acid is not harmful. Funding Funders are shown in the appendix.

Background: Global dietary recommendations for and cardiovascular effects of linoleic acid, the major dietary omega-6 fatty acid, and its major metabolite, arachidonic acid, remain controversial. To address this uncertainty and inform international recommendations, we evaluated how in vivo circulating and tissue levels of linoleic acid (LA) and arachidonic acid (AA) relate to incident cardiovascular disease (CVD) across multiple international studies. Methods: We performed harmonized, de novo, individual-level analyses in a global consortium of 30 prospective observational studies from 13 countries. Multivariable-adjusted associations of circulating and adipose tissue LA and AA biomarkers with incident total CVD and subtypes (coronary heart disease (CHD), ischemic stroke, cardiovascular mortality) were investigated according to a prespecified analytical plan. Levels of LA and AA, measured as % of total fatty acids, were evaluated linearly according to their interquintile range (i.e., the range between the mid-point of the first and fifth quintiles), and categorically by quintiles. Study-specific results were pooled using inverse-variance weighted meta-analysis. Heterogeneity was explored by age, sex, race, diabetes, statin use, aspirin use, omega-3 levels, and fatty acid desaturase 1 genotype (when available). Results: In 30 prospective studies with medians of follow-up ranging 2.5 to 31.9 years, 15,198 incident cardiovascular events occurred among 68,659 participants. Higher levels of LA were significantly associated with lower risks of total CVD, cardiovascular mortality, and ischemic stroke, with hazard ratios per interquintile range of 0.93 (95% CI: 0.88-0.99), 0.78 (0.70-0.85), and 0.88 (0.79-0.98), respectively, and nonsignificantly with lower CHD risk (0.94; 0.88-1.00). Relationships were similar for LA evaluated across quintiles. AA levels were not associated with higher risk of cardiovascular outcomes; comparing extreme quintiles, higher levels were associated with lower risk of total CVD (0.92; 0.86-0.99). No consistent heterogeneity by population subgroups was identified in the observed relationships. Conclusions: In pooled global analyses, higher in vivo circulating and tissue levels of LA and possibly AA were associated with lower risk of major cardiovascular events. These results support a favorable role for LA in CVD prevention. What is new?• We conducted the hitherto largest pooled individual-level analysis using circulating and adipose tissue levels of linoleic acid and arachidonic acid to examine the link between omega-6 fatty acids and cardiovascular outcomes in various populations.• Our approach increases statistical power and generalizability compared to individual studies; lowers the risk of publication bias and heterogeneity compared to metaanalyses of existing literature; and allows evaluation of the associations in key population subgroups.• Strikingly, higher level of linoleic acid was associated with lower risks of total cardiovascular disease, ischemic stroke, and cardiovascular mortal...

Background Saturated fatty acids (SFAs) of different chain lengths have unique metabolic and biological effects, and a small number of recent studies suggest that higher circulating concentrations of the very-long-chain SFAs (VLSFAs) arachidic acid (20:0), behenic acid (22:0), and lignoceric acid (24:0) are associated with a lower risk of diabetes. Confirmation of these findings in a large and diverse population is needed. Objective We investigated the associations of circulating VLSFAs 20:0, 22:0, and 24:0 with incident type 2 diabetes in prospective studies. Methods Twelve studies that are part of the Fatty Acids and Outcomes Research Consortium participated in the analysis. Using Cox or logistic regression within studies and an inverse-variance-weighted meta-analysis across studies, we examined the associations of VLSFAs 20:0, 22:0, and 24:0 with incident diabetes among 51,431 participants. Results There were 14,276 cases of incident diabetes across participating studies. Higher circulating concentrations of 20:0, 22:0, and 24:0 were each associated with a lower risk of incident diabetes. Pooling across cohorts, the RR (95% CI) for incident diabetes comparing the 90th percentile to the 10th percentile was 0.78 (0.70, 0.87) for 20:0, 0.84 (0.77, 0.91) for 22:0, and 0.75 (0.69, 0.83) for 24:0 after adjustment for demographic, lifestyle, adiposity, and other health factors. Results were fully attenuated in exploratory models that adjusted for circulating 16:0 and triglycerides. Conclusions Results from this pooled analysis indicate that higher concentrations of circulating VLSFAs 20:0, 22:0, and 24:0 are each associated with a lower risk of diabetes.

Recent analyses have suggested a strong heritable component to circulating fatty acid (FA) levels; however, only a limited number of genes have been identified which associate with FA levels. In order to expand upon a previous genome wide association study done on participants in the Framingham Heart Study Offspring Cohort and FA levels, we used data from 2,400 of these individuals for whom red blood cell FA profiles, dietary information and genotypes are available, and then conducted a genome-wide evaluation of potential genetic variants associated with 22 FAs and 15 FA ratios, after adjusting for relevant dietary covariates. Our analysis found nine previously identified loci associated with FA levels (FADS, ELOVL2, PCOLCE2, LPCAT3, AGPAT4, NTAN1/PDXDC1, PKD2L1, HBS1L/MYB and RAB3GAP1/MCM6), while identifying four novel loci. The latter include an association between variants in CALN1 (Chromosome 7) and eicosapentaenoic acid (EPA), DHRS4L2 (Chromosome 14) and a FA ratio measuring delta-9-desaturase activity, as well as two loci associated with less well understood proteins. Thus, the inclusion of dietary covariates had a modest impact, helping to uncover four additional loci. While genome-wide association studies continue to uncover additional genes associated with circulating FA levels, much of the heritable risk is yet to be explained, suggesting the potential role of rare genetic variation, epistasis and gene-environment interactions on FA levels as well. Further studies are needed to continue to understand the complex genetic picture of FA metabolism and synthesis.

Numerous genetic loci have been identified as being associated with circulating fatty acid (FA) levels and/or inflammatory biomarkers of cardiovascular health (e.g., C-reactive protein). Recently, using red blood cell (RBC) FA data from the Framingham Offspring Study, we conducted a genome-wide association study of over 2.5 million single nucleotide polymorphisms (SNPs) and 22 RBC FAs (and associated ratios), including the four Omega-3 FAs (ALA, DHA, DPA, and EPA). Our analyses identified numerous causal loci. In this manuscript, we investigate the extent to which polyunsaturated fatty acid (PUFA) levels moderate the relationship of genetics to cardiovascular health biomarkers using a genome-wide interaction study approach. In particular, we test for possible gene–FA interactions on 9 inflammatory biomarkers, with 2.5 million SNPs and 12 FAs, including all Omega-3 PUFAs. We identified eighteen novel loci, including loci which demonstrate strong evidence of modifying the impact of heritable genetics on biomarker levels, and subsequently cardiovascular health. The identified genes provide increased clarity on the biological functioning and role of Omega-3 PUFAs, as well as other common fatty acids, in cardiovascular health, and suggest numerous candidate loci for future replication and biological characterization.

In the search for an understanding of how genetic variation contributes to the heritability of common human disease, the potential role of epigenetic factors, such as methylation, is being explored with increasing frequency. Although standard analyses test for associations between methylation levels at individual cytosine-phosphate-guanine (CpG) sites and phenotypes of interest, some investigators have begun testing for methylation and how methylation may modulate the effects of genetic polymorphisms on phenotypes. In our analysis, we used both a genome-wide and candidate gene approach to investigate potential single-nucleotide polymorphism (SNP)–CpG interactions on changes in triglyceride levels. Although we were able to identify numerous loci of interest when using an exploratory significance threshold, we did not identify any significant interactions using a strict genome-wide significance threshold. We were also able to identify numerous loci using the candidate gene approach, in which we focused on 18 genes with prior evidence of association of triglyceride levels. In particular, we identified GALNT2 loci as containing potential CpG sites that moderate the impact of genetic polymorphisms on triglyceride levels. Further work is needed to provide clear guidance on analytic strategies for testing SNP–CpG interactions, although leveraging prior biological understanding may be needed to improve statistical power in data sets with smaller sample sizes.

BackgroundGAW20 working group 5 brought together researchers who contributed 7 papers with the aim of evaluating methods to detect genetic by epigenetic interactions. GAW20 distributed real data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, including single-nucleotide polymorphism (SNP) markers, methylation (cytosine-phosphate-guanine [CpG]) markers, and phenotype information on up to 995 individuals. In addition, a simulated data set based on the real data was provided.ResultsThe 7 contributed papers analyzed these data sets with a number of different statistical methods, including generalized linear mixed models, mediation analysis, machine learning, W-test, and sparsity-inducing regularized regression. These methods generally appeared to perform well. Several papers confirmed a number of causative SNPs in either the large number of simulation sets or the real data on chromosome 11. Findings were also reported for different SNPs, CpG sites, and SNP–CpG site interaction pairs.ConclusionsIn the simulation (200 replications), power appeared generally good for large interaction effects, but smaller effects will require larger studies or consortium collaboration for realizing a sufficient power.

Although methylation data continues to rise in popularity, much is still unknown about how to best analyze methylation data in genome-wide analysis contexts. Given continuing interest in gene-based tests for next-generation sequencing data, we evaluated the performance of novel gene-based test statistics on simulated data from GAW20. Our analysis suggests that most of the gene-based tests are detecting real signals and maintaining the Type I error rate. The minimum p value and threshold-based tests performed well compared to single-marker tests in many cases, especially when the number of variants was relatively large with few true causal variants in the set.