Instituto Madrileno Of Estudios Avanzados Alimentacion

Madrid, Spain

Instituto Madrileno Of Estudios Avanzados Alimentacion

Madrid, Spain
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Aslibekyan S.,University of Alabama at Birmingham | Goodarzi M.O.,Cedars Sinai Medical Center | Frazier-Wood A.C.,University of Alabama at Birmingham | Yan X.,Cedars Sinai Medical Center | And 15 more authors.
PLoS ONE | Year: 2012

A recent large-scale meta-analysis of genome-wide studies has identified 95 loci, 59 of them novel, as statistically significant predictors of blood lipid traits; we tested whether the same loci explain the observed heterogeneity in response to lipid-lowering therapy with fenofibrate. Using data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, n = 861) we fit linear mixed models with the genetic markers as predictors and high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, total cholesterol, and triglyceride concentrations as outcomes. For all four traits, we analyzed both baseline levels and changes in response to treatment with fenofibrate. For the markers that were significantly associated with fenofibrate response, we fit additional models evaluating potential epistatic interactions. All models were adjusted for age, sex, and study center as fixed effects, and pedigree as a random effect. Statistically significant associations were observed between the rs964184 polymorphism near APOA1 (P-value≤0.0001) and fenofibrate response for HDL and triglycerides. The association was replicated in the Pharmacogenetics of Hypertriglyceridemia in Hispanics study (HyperTG, n = 267). Suggestive associations with fenofibrate response were observed for markers in or near PDE3A, MOSC1, FLJ36070, CETP, the APOE-APOC1-APOC4-APOC2, and CILP2. Finally, we present strong evidence for epistasis (P-value for interaction = 0.0006 in GOLDN, 0.05 in HyperTG) between rs10401969 near CILP2 and rs4420638 in the APOE-APOC1-APOC4-APOC2 cluster with total cholesterol response to fenofibrate. In conclusion, we present evidence linking several novel and biologically relevant genetic polymorphisms to lipid lowering drug response, as well as suggesting novel gene-gene interactions in fenofibrate pharmacogenetics. © 2012 Aslibekyan et al.

Zheng J.-S.,Tufts University | Zheng J.-S.,Zhejiang University | Lai C.-Q.,Tufts University | Parnell L.D.,Tufts University | And 14 more authors.
BMC Genomics | Year: 2014

Background: Little is known about the interplay between n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level. The present study aimed to examine variance contributions of genotype by environment (GxE) interactions for different erythrocyte n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level in a non-Hispanic white population living in the U.S.A. (n = 820). A tool for Genome-wide Complex Trait Analysis (GCTA) was used to estimate the genome-wide GxE variance contribution of four diabetes-related traits: HOMA-Insulin Resistance (HOMA-IR), fasting plasma insulin, glucose and adiponectin. A GxE genome-wide association study (GWAS) was conducted to further elucidate the GCTA results. Replication was conducted in the participants of the Boston Puerto Rican Health Study (BPRHS) without diabetes (n = 716). Results: In GOLDN, docosapentaenoic acid (DPA) contributed the most significant GxE variance to the total phenotypic variance of both HOMA-IR (26.5%, P-nominal = 0.034) and fasting insulin (24.3%, P-nominal = 0.042). The ratio of arachidonic acid to eicosapentaenoic acid + docosahexaenoic acid contributed the most significant GxE variance to the total variance of fasting glucose (27.0%, P-nominal = 0.023). GxE variance of the arachidonic acid/eicosapentaenoic acid ratio showed a marginally significant contribution to the adiponectin variance (16.0%, P-nominal = 0.058). None of the GCTA results were significant after Bonferroni correction (P < 0.001). For each trait, the GxE GWAS identified a far larger number of significant single-nucleotide polymorphisms (P-interaction ≤ 10E-5) for the significant E factor (significant GxE variance contributor) than a control E factor (non-significant GxE variance contributor). In the BPRHS, DPA contributed a marginally significant GxE variance to the phenotypic variance of HOMA-IR (12.9%, P-nominal = 0.068) and fasting insulin (18.0%, P-nominal = 0.033).Conclusion: Erythrocyte n-3 fatty acids contributed a significant GxE variance to diabetes-related traits at the genome-wide level. © 2014 Zheng et al.; licensee BioMed Central Ltd.

Crosby J.,University of Houston | Crosby J.,University of Texas Health Science Center at Houston | Peloso G.M.,Massachusetts General Hospital | Peloso G.M.,Harvard University | And 107 more authors.
New England Journal of Medicine | Year: 2014

BACKGROUND: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype. METHODS: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons. RESULTS: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G→A and IVS3+1G→T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1×10-20), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10 -10). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P=4×10-6). CONCLUSIONS: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. Copyright © 2014 Massachusetts Medical Society.

Casas-Agustench P.,Tufts University | Arnett D.K.,Instituto Madrileno Of Estudios Avanzados Alimentacion | Smith C.E.,University of Alabama at Birmingham | Lai C.-Q.,Instituto Madrileno Of Estudios Avanzados Alimentacion | And 13 more authors.
Journal of the Academy of Nutrition and Dietetics | Year: 2014

Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and body mass index (BMI) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake, and to replicate findings in the Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 white US participants from GOLDN and 2,035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA, and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA, and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although determining the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs. © 2014 Academy of Nutrition and Dietetics.

Aslibekyan S.,University of Alabama at Birmingham | Demerath E.W.,University of Minnesota | Mendelson M.,U.S. National Institutes of Health | Mendelson M.,Boston Childrens Hospital | And 28 more authors.
Obesity | Year: 2015

Objective To conduct an epigenome-wide analysis of DNA methylation and obesity traits. Methods DNA methylation was quantified in CD4+ T-cells using the Illumina Infinium HumanMethylation450 array in 991 participants of the Genetics of Lipid Lowering Drugs and Diet Network. Methylation at individual cytosine-phosphate-guanine (CpG) sites as a function of body mass index (BMI) and waist circumference (WC), adjusting for age, gender, study site, T-cell purity, smoking, and family structure, was modeled. Results Epigenome-wide significant associations between eight CpG sites and BMI and five CpG sites and WC, successfully replicating the top hits in whole blood samples from the Framingham Heart Study (n-=-2,377) and the Atherosclerosis Risk in Communities study (n-=-2,097), were found. Top findings were in CPT1A (meta-analysis P-=-2.7 × 10-43 for BMI and 9.9 × 10-23 for WC), PHGDH (meta-analysis P-=-2.0 × 10-15 for BMI and 4.0 × 10-9 for WC), CD38 (meta-analysis P-=-6.3 × 10-11 for BMI and 1.6 × 10-12 for WC), and long intergenic non-coding RNA 00263 (meta-analysis P-=-2.2 × 10-16 for BMI and 8.9 × 10-14 for WC), regions with biologically plausible relationships to adiposity. Conclusions This large-scale epigenome-wide study discovered and replicated robust associations between DNA methylation at CpG loci and obesity indices, laying the groundwork for future diagnostic and/or therapeutic applications. © 2015 The Obesity Society.

Irvin M.R.,University of Alabama at Birmingham | Zhi D.,University of Alabama at Birmingham | Aslibekyan S.,University of Alabama at Birmingham | Claas S.A.,University of Alabama at Birmingham | And 7 more authors.
PLoS ONE | Year: 2014

Background: Increased postprandial lipid (PPL) response to dietary fat intake is a heritable risk factor for cardiovascular disease (CVD). Variability in postprandial lipids results from the complex interplay of dietary and genetic factors. We hypothesized that detailed lipid profiles (eg, sterols and fatty acids) may help elucidate specific genetic and dietary pathways contributing to the PPL response. Methods and Results: We used gas chromatography mass spectrometry to quantify the change in plasma concentration of 35 fatty acids and 11 sterols between fasting and 3.5 hours after the consumption of a high-fat meal (PPL challenge) among 40 participants from the GOLDN study. Correlations between sterols, fatty acids and clinical measures were calculated. Mixed linear regression was used to evaluate associations between lipidomic profiles and genomic markers including single nucleotide polymorphisms (SNPs) and methylation markers derived from the Affymetrix 6.0 array and the Illumina Methyl450 array, respectively. After the PPL challenge, fatty acids increased as well as sterols associated with cholesterol absorption, while sterols associated with cholesterol synthesis decreased. PPL saturated fatty acids strongly correlated with triglycerides, very low-density lipoprotein, and chylomicrons. Two SNPs (rs12247017 and rs12240292) in the sorbin and SH3 domain containing 1 (SORBS1) gene were associated with b-Sitosterol after correction for multiple testing (P≤4.5*10-10). SORBS1 has been linked to obesity and insulin signaling. No other markers reached the genome-wide significance threshold, yet several other biologically relevant loci are highlighted (eg, PRIC285, a co-activator of PPARa). Conclusions: Integration of lipidomic and genomic data has the potential to identify new biomarkers of CVD risk. © 2014 Irvin et al.

Aslibekyan S.,University of Alabama at Birmingham | An P.,Washington University in St. Louis | Frazier-Wood A.C.,University of Alabama at Birmingham | Kabagambe E.K.,University of Alabama at Birmingham | And 10 more authors.
Nutrition, Metabolism and Cardiovascular Diseases | Year: 2013

Background and aims: Adiponectin is an adipose-secreted protein that has been linked to changes in insulin sensitivity, high-density lipoprotein cholesterol levels, and inflammatory patterns. Although fenofibrate therapy can raise adiponectin levels, treatment response is heterogeneous and heritable, suggesting a role for genetic mediators. This is the first genome-wide association study of fenofibrate effects on circulating adiponectin. Methods and results: Plasma adiponectin was measured in participants of the Genetics of Lipid Lowering Drugs and Diet Network (n=793) before and after a 3-week daily treatment with 160mg of fenofibrate. Associations between variants on the Affymetrix Genome-Wide Human SNP Array 6.0 and adiponectin were assessed using mixed linear models, adjusted for age, sex, site, and family. We observed a statistically significant (P=5×10-8) association between rs2384207 in 12q24, a region previously linked to several metabolic traits, and the fenofibrate-induced change in circulating adiponectin. Additionally, our genome-wide analysis of baseline adiponectin levels replicated the previously reported association with CDH13 and suggested novel associations with markers near the PCK1, ZBP1, TMEM18, and SCUBE1 genes. The findings from the single marker tests were corroborated in gene-based analyses. Biological pathway analyses suggested a borderline significant association between the EGF receptor signaling pathway and baseline adiponectin levels. Conclusions: We present preliminary evidence linking several biologically relevant genetic variants to adiponectin levels at baseline and in response to fenofibrate therapy. Our findings provide support for fine-mapping of the 12q24 region to investigate the shared biological mechanisms underlying levels of circulating adiponectin and susceptibility to metabolic disease. © 2012 Elsevier B.V.

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