A lipidome-wide association study of the lipoprotein insulin resistance index.

BACKGROUND: The lipoprotein insulin resistance (LPIR) score was shown to predict insulin resistance (IR) and type 2 diabetes (T2D) in healthy adults. However, the molecular basis underlying the LPIR utility for classification remains unclear. OBJECTIVE: To identify small molecule lipids associated with variation in the LPIR score, a weighted index of lipoproteins measured by nuclear magnetic resonance, in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (n = 980). METHODS: Linear mixed effects models were used to test the association between the LPIR score and 413 lipid species and their principal component analysis-derived groups. Significant associations were tested for replication with homeostatic model assessment-IR (HOMA-IR), a phenotype correlated with the LPIR score (r = 0.48, p <  0.001), in the Heredity and Phenotype Intervention (HAPI) Heart Study (n = 590). RESULTS: In GOLDN, 319 lipids were associated with the LPIR score (false discovery rate-adjusted p-values ranging from 4.59 × 10- 161 to 49.50 × 10- 3). Factors 1 (triglycerides and diglycerides/storage lipids) and 3 (mixed lipids) were positively (ß = 0.025, p = 4.52 × 10- 71 and ß = 0.021, p = 5.84 × 10- 41, respectively) and factor 2 (phospholipids/non-storage lipids) was inversely (ß = - 0.013, p = 2.28 × 10- 18) associated with the LPIR score. These findings were replicated for HOMA-IR in the HAPI Heart Study (ß = 0.10, p = 1.21 × 10- 02 for storage, ß = - 0.13, p = 3.14 × 10- 04 for non-storage, and ß = 0.19, p = 8.40 × 10- 07 for mixed lipids). CONCLUSIONS: Non-storage lipidomics species show a significant inverse association with the LPIR metabolic dysfunction score and present a promising focus for future therapeutic and prevention studies.

Detecting responses to treatment with fenofibrate in pedigrees.

BACKGROUND: Fenofibrate (Fb) is a known treatment for elevated triglyceride (TG) levels. The Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study was designed to investigate potential contributors to the effects of Fb on TG levels. Here, we summarize the analyses of 8 papers whose authors had access to the GOLDN data and were grouped together because they pursued investigations into Fb treatment responses as part of GAW20. These papers report explorations of a variety of genetics, epigenetics, and study design questions. Data regarding treatment with 160 mg of micronized Fb per day for 3 weeks included pretreatment and posttreatment TG and methylation levels (ML) at approximately 450,000 epigenetic markers (cytosine-phosphate-guanine [CpG] sites). In addition, approximately 1 million single-nucleotide polymorphisms (SNPs) were genotyped or imputed in each of the study participants, drawn from 188 pedigrees. RESULTS: The analyses of a variety of subsets of the GOLDN data used a number of analytic approaches such as linear mixed models, a kernel score test, penalized regression, and artificial neural networks. CONCLUSIONS: Results indicate that (a) CpG ML are responsive to Fb; (b) CpG ML should be included in models predicting the TG level responses to Fb;

Detection of gene-environment interactions in a family-based population using SCAD.

Gene-environment interaction (GxE) is emphasized as one potential source of missing genetic variation on disease traits, and the ultimate goal of GxE research is prediction of individual risk and prevention of complex diseases. However, there are various challenges in statistical analysis of GxE. In this paper, we focus on the three methodological challenges: (i) the high dimensions of genes; (ii) the hierarchical structure between interaction effects and their corresponding main effects; and (iii) the correlation among subjects from family-based population studies. In this paper, we propose an algorithm that approaches all three challenges simultaneously. This is the first penalized method focusing on an interaction search based on a linear mixed effect model. For verification, we compare the empirical performance of our new method with other existing methods in simulation study. The results demonstrate the superiority of our method under overall simulation setup. In particular, the outperformance obviously becomes greater as the correlation among subjects increases. In addition, the new method provides a robust estimate for the correlation among subjects. We also apply the new method on Genetics of Lipid Lowering Drugs and Diet Network study data. Copyright © 2017 John Wiley & Sons, Ltd.

The association between LRP-1 variants and chylomicron uptake after a high fat meal.

BACKGROUND AND AIMS: In vitro studies suggest that low density lipoprotein receptor-related protein 1 (LRP1) plays a role in the secondary uptake of chylomicrons. In addition, in vivo studies using LRP-1 knockout mice show these animals exhibit delayed chylomicron clearance. Whether this is true in humans is unknown. We aimed to determine whether genetic variants in LRP-1 are associated with postprandial chylomicron uptake in humans given an oral fat challenge. METHODS AND RESULTS: As many as 817 men and women (mean age +/- standard deviation = 48.4 +/- 16.4 years) forming the study population for the Genetics of Lipid Lowering Drugs Network (GOLDN) study ingested an oral fat load of 700 kilocalories per m² of body surface area at 83% fat, after an 8-h fast. Chylomicrons were measured by nuclear resonance spectroscopy (NMR) at fasting, and 3.5 and 6 h after the meal. 26 Single nucleotide polymorphisms (SNPs) in the LRP-1 gene were genotyped on the Affymetrix 6.0 array. Chylomicrons were, as expected, zero at fasting. Mixed linear models adjusted for age, sex, study site and pedigree tested for associations between LRP-1 SNPs and changes in chylomicron concentrations 3.5-6 h. A gene-based test across all 26 SNPs was conducted which corrected for the linkage disequilibrium (LD) between SNPs. 11 LRP-1 SNPs were significantly associated with the change in chylomicron concentration correction for multiple testing (Q < 0.05). The subsequent gene-based test, was also significant (P = 0.01). CONCLUSION: These results require replication but strongly indicate the role of LRP1 in postprandial lipoprotein uptake and/or clearance.

The integration of epigenetics and genetics in nutrition research for CVD risk factors.

There is increasing evidence documenting gene-by-environment (G × E) interactions for CVD related traits. However, the underlying mechanisms are still unclear. DNA methylation may represent one of such potential mechanisms. The objective of this review paper is to summarise the current evidence supporting the interplay among DNA methylation, genetic variants, and environmental factors, specifically (1) the association between SNP and DNA methylation; (2) the role that DNA methylation plays in G × E interactions. The current evidence supports the notion that genotype-dependent methylation may account, in part, for the mechanisms underlying observed G × E interactions in loci such as APOE, IL6 and ATP-binding cassette A1. However, these findings should be validated using intervention studies with high level of scientific evidence. The ultimate goal is to apply the knowledge and the technology generated by this research towards genetically based strategies for the development of personalised nutrition and medicine.

Assessment of postprandial triglycerides in clinical practice: Validation in a general population and coronary heart disease patients.

BACKGROUND: Previous studies have suggested that for clinical purposes, subjects with fasting triglycerides (TGs) between 89-180 mg/dl (1-2 mmol/l) would benefit from postprandial TGs testing. OBJECTIVE: To determine the postprandial TG response in 2 independent studies and validate who should benefit diagnostically from an oral-fat tolerance test (OFTT) in clinical practice. METHODS: A population of 1002 patients with coronary heart disease (CHD) from the CORDIOPREV clinical trial and 1115 white US subjects from the GOLDN study underwent OFTTs. Subjects were classified into 3 groups according to fasting cut points of TGs to predict the usefulness of OFTT: (1) TG < 89 mg/dl (<1 mmol/l); (2) TG, 89-180 mg/dl (1-2 mmol/l); and (3) TG > 180 mg/dl (>2 mmol/l). Postprandial TG concentration at any point > 220 mg/dl (>2.5 mmol/l) has been pre-established as an undesirable postprandial response. RESULTS: Of the total, 49% patients with CHD and 42% from the general population showed an undesirable response after the OFTT. The prevalence of undesirable postprandial TG in the CORDIOPREV clinical trial was 12.8, 50.3, and 89.7%, in group 1, 2, and 3, respectively (P < .001) and 11.2, 58.1, and 97.5% in group 1, 2, and 3, respectively (P < .001) in the GOLDN study. CONCLUSIONS: These two studies validate the predictive values reported in a previous consensus. Moreover, the findings of the CORDIOPREV and GOLDN studies show that an OFTT is useful to identify postprandial hyperlipidemia in subjects with fasting TG between 1-2 mmol/l (89-180 mg/dL), because approximately half of them have hidden postprandial hyperlipidemia, which may influence treatment. An OFTT does not provide additional information regarding postprandial hyperlipidemia in subjects with low TG (<1 mmol/l, <89 mg/dL) or increased TG (>2 mmol/l, >180 mg/dl).