409 research outputs found

    Evaluation of diet pattern and weight gain in postmenopausal women enrolled in the Women’s Health Initiative Observational Study

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    Abstract It is unclear which of four popular contemporary diet patterns is best for weight maintenance among postmenopausal women. Four dietary patterns were characterised among postmenopausal women aged 49–81 years (mean 63·6 ( sd 7·4) years) from the Women’s Health Initiative Observational Study: (1) a low-fat diet; (2) a reduced-carbohydrate diet; (3) a Mediterranean-style (Med) diet; and (4) a diet consistent with the US Department of Agriculture’s Dietary Guidelines for Americans (DGA). Discrete-time hazards models were used to compare the risk of weight gain (≥10 %) among high adherers of each diet pattern. In adjusted models, the reduced-carbohydrate diet was inversely related to weight gain (OR 0·71; 95 % CI 0·66, 0·76), whereas the low-fat (OR 1·43; 95 % CI 1·33, 1·54) and DGA (OR 1·24; 95 % CI 1·15, 1·33) diets were associated with increased risk of weight gain. By baseline weight status, the reduced-carbohydrate diet was inversely related to weight gain among women who were normal weight (OR 0·72; 95 % CI 0·63, 0·81), overweight (OR 0·67; 95 % CI 0·59, 0·76) or obese class I (OR 0·63; 95 % CI 0·53, 0·76) at baseline. The low-fat diet was associated with increased risk of weight gain in women who were normal weight (OR 1·28; 95 % CI 1·13, 1·46), overweight (OR 1·60; 95 % CI 1·40, 1·83), obese class I (OR 1·73; 95 % CI 1·43, 2·09) or obese class II (OR 1·44; 95 % CI 1·08, 1·92) at baseline. These findings suggest that a low-fat diet may promote weight gain, whereas a reduced-carbohydrate diet may decrease risk of postmenopausal weight gain

    Genetic risk scores associated with baseline lipoprotein subfraction concentrations do not associate with their responses to fenofibrate

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    Lipoprotein subclass concentrations are modifiable markers of cardiovascular disease risk. Fenofibrate is known to show beneficial effects on lipoprotein subclasses, but little is known about the role of genetics in mediating the responses of lipoprotein subclasses to fenofibrate. A recent genomewide association study (GWAS) associated several single nucleotide polymorphisms (SNPs) with lipoprotein measures, and validated these associations in two independent populations. We used this information to construct genetic risk scores (GRSs) for fasting lipoprotein measures at baseline (pre-fenofibrate), and aimed to examine whether these GRSs also associated with the responses of lipoproteins to fenofibrate. Fourteen lipoprotein subclass measures were assayed in 817 men and women before and after a three week fenofibrate trial. We set significance at a Bonferroni corrected alpha <0.05 (p < 0.004). Twelve subclass measures changed with fenofibrate administration (each p = 0.003 to <0.0001). Mixed linear models which controlled for age, sex, body mass index (BMI), smoking status, pedigree and study-center, revealed that GRSs were associated with eight baseline lipoprotein measures (p < 0.004), however no GRS was associated with fenofibrate response. These results suggest that the mechanisms for changes in lipoprotein subclass concentrations with fenofibrate treatment are not mediated by the genetic risk for fasting levels

    A clustering analysis of lipoprotein diameters in the metabolic syndrome

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    <p>Abstract</p> <p>Background</p> <p>The presence of smaller low-density lipoproteins (LDL) has been associated with atherosclerosis risk, and the insulin resistance (IR) underlying the metabolic syndrome (MetS). In addition, some research has supported the association of very low-, low- and high-density lipoprotein (VLDL HDL) particle diameters with components of the metabolic syndrome (MetS), although this has been the focus of less research. We aimed to explore the relationship of VLDL, LDL and HDL diameters to MetS and its features, and by clustering individuals by their diameters of VLDL, LDL and HDL particles, to capture information across all three fractions of lipoprotein into a unified phenotype.</p> <p>Methods</p> <p>We used nuclear magnetic resonance spectroscopy measurements on fasting plasma samples from a general population sample of 1,036 adults (mean ± SD, 48.8 ± 16.2 y of age). Using latent class analysis, the sample was grouped by the diameter of their fasting lipoproteins, and mixed effects models tested whether the distribution of MetS components varied across the groups.</p> <p>Results</p> <p>Eight discrete groups were identified. Two groups (N = 251) were enriched with individuals meeting criteria for the MetS, and were characterized by the smallest LDL/HDL diameters. One of those two groups, one was additionally distinguished by large VLDL, and had significantly higher blood pressure, fasting glucose, triglycerides, and waist circumference (WC; <it>P </it>< .001). However, large VLDL, in the absence of small LDL and HDL particles, did not associate with MetS features. These associations held after additionally controlling for VLDL, LDL and HDL particle concentrations.</p> <p>Conclusions</p> <p>While small LDL diameters remain associated with IR and the MetS, the occurrence of these in conjunction with a shift to overall larger VLDL diameter may identify those with the highest fasting glucose, TG and WC within the MetS. If replicated, the association of this phenotype with more severe IR-features indicated that it may contribute to identifying of those most at risk for incident type II diabetes and cardiometabolic disease.</p

    An Exome-Wide Sequencing Study of Lipid Response to High-Fat Meal and Fenofibrate in Caucasians from the GOLDN Cohort

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    Our understanding of genetic influences on the response of lipids to specific interventions is limited. In this study, we sought to elucidate effects of rare genetic variants on lipid response to a high-fat meal challenge and fenofibrate (FFB) therapy in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) cohort using an exome-wide sequencing-based association study. Our results showed that the rare coding variants in ITGA7, SIPA1L2, and CEP72 are significantly associated with fasting LDL cholesterol response to FFB (P = 1.24E-07), triglyceride postprandial area under the increase (AUI) (P = 2.31E-06), and triglyceride postprandial AUI response to FFB (P = 1.88E-06), respectively. We sought to replicate the association for SIPA1L2 in the Heredity and Phenotype Intervention (HAPI) Heart Study, which included a high-fat meal challenge but not FFB treatment. The associated rare variants in GOLDN were not observed in the HAPI Heart study, and thus the gene-based result was not replicated. For functional validation, we found that gene transcript level of SIPA1L2 is associated with triglyceride postprandial AUI (P \u3c 0.05) in GOLDN. Our study suggests unique genetic mechanisms contributing to the lipid response to the high-fat meal challenge and FFB therapy

    Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

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    Scope: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter‐individual variability in associations between body weight and dairy consumption. Methods and results: A genome‐wide interaction study to discover genetic variants that account for variation in BMI in the context of low‐fat, high‐fat and total dairy intake in cross‐sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta‐analyzed. Twenty‐six genetic variants reached the selected significance threshold (p‐interaction \u3c10−7), and six independent variants (LINC01512‐rs7751666, PALM2/AKAP2‐rs914359, ACTA2‐rs1388, PPP1R12A‐rs7961195, LINC00333‐rs9635058, AC098847.1‐rs1791355) were evaluated meta‐analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3’ of LINC00333) was replicated (p‐interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p‐interaction = 7.36 × 10−8) such that each serving of low‐fat dairy was associated with 0.225 kg m−2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2‐rs1388) approached interaction replication significance for low‐fat dairy exposure. Conclusion: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight

    Discovery and fine-mapping of loci associated with MUFAs through trans-ethnic meta-analysis in Chinese and European populations

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    MUFAs are unsaturated FAs with one double bond and are derived from endogenous synthesis and dietary intake. Accumulating evidence has suggested that plasma and erythrocyte MUFA levels are associated with cardiometabolic disorders, including CVD, T2D, and metabolic syndrome (MS). Previous genome-wide association studies (GWASs) have identified seven loci for plasma and erythrocyte palmitoleic and oleic acid levels in populations of European origin. To identify additional MUFA-associated loci and the potential functional variant at each locus, we performed ethnic-specific GWAS meta-analyses and trans-ethnic meta-analyses in more than 15,000 participants of Chinese and European ancestry. We identified novel genome-wide significant associations for vaccenic acid at FADS1/2 and PKD2L1 [log(10)(Bayes factor). >= 8.07] and for gondoic acid at FADS1/2 and GCKR [log(10)(Bayes factor) >= 6.22], and also observed improved fine-mapping resolutions at FADS1/2 and GCKR loci. The greatest improvement was observed at GCKR, where the number of variants in the 99\% credible set was reduced from 16 (covering 94.8 kb) to 5 (covering 19.6 kb, including a missense variant rs1260326) after trans-ethnic meta-analysis. We also confirmed the previously reported associations of PKD2L1, FADS1/2, GCKR, and HIF1AN with palmitoleic acid and of FADS1/2 and LPCAT3 with oleic acid in the Chinese-specific GWAS and the trans-ethnic meta-analyses. Pathway-based analyses suggested that the identified loci were in unsaturated FA metabolism and signaling pathways.(jl) Our findings provide novel insight into the genetic basis relevant to MUFA metabolism and biology.Infrastructure for the CHARGE Consortium was supported in part by the National Heart, Lung, and Blood Institute grant HL105756. The NHAPC study was supported by the major project of the Ministry of Science and Technology of China (2016YFC1304903) and the National Natural Science Foundation of China (81471013, 30930081, 81170734, and 81321062). The ARIC Study was carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C and grants R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. Infrastructure was partly supported by grant UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. The CARDIA study was conducted and supported by the National Heart, Lung, and Blood Institute in collaboration with the University of Alabama at Birmingham (HHSN268201300025C and HHSN268201300026C), Northwestern University (HHSN268201300027C), University of Minnesota (HHSN268201300028C), Kaiser Foundation Research Institute (HHSN268201300029C), and Johns Hopkins University School of Medicine (HHSN268200900041C). CARDIA is also partially supported by the Intramural Research Program of the National Institute on Aging. Genotyping of the CARDIA participants was supported by National Human Genome Research Institute grants U01-HG-004729, U01-HG-004446, and U01-HG-004424. Statistical analyses and FA measures were funded by National Heart, Lung, and Blood Institute grant R01-HL-084099 (M.F.). The CHS was supported by National Heart, Lung, and Blood Institute contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, and N01HC85086; and National Heart, Lung, and Blood Institute grants U01HL080295, R01HL087652, R01HL105756, R01HL103612, R01HL120393, and R01HL085710, with additional contribution from the National Institute of Neurological Disorders and Stroke. Additional support was provided through National Institute on Aging grant R01AG023629. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences CTSI grant UL1TR000124 and the National Institute of Diabetes and Digestive and Kidney Diseases Diabetes Research Center grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The HPFS and NHS were supported by National Institutes of Health research grants UM1 CA186107, R01 HL034594, UM1 CA167552, R01 HL35464, HL60712, and CA055075; National Heart, Lung, and Blood Institute career development award R00HL098459; American Diabetes Association research grant 1-12-JF-13; and American Heart Association grant 11SDG7380016. The MESA study and MESA SHARe were supported by National Heart, Lung, and Blood Institute contracts N01-HC-95159 through N01-HC-95169 and RR-024156. Funding for MESA SHARe genotyping was provided by National Heart, Lung, and Blood Institute contract N02HL64278. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences CTSI grant UL1TR000124 and the National Institute of Diabetes and Digestive and Kidney Diseases Diabetes Research Center grant DK063491 (Southern California Diabetes Endocrinology Research Center).; The GOLDN study was funded by National Heart, Lung, and Blood Institute grants U01HL072524 and HL54776. The InCHIANTI baseline (1998-2000) was supported as a ``targeted project (ICS110.1/RF97.71) by the Italian Ministry of Health and in part by National Institute on Aging contracts 263 MD 9164 and 263 MD 821336. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.S

    Meta-analysis across Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium provides evidence for an association of serum vitamin D with pulmonary function

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    The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for serum 25-hydroxyvitamin D (25(OH)D)-pulmonary function association. We conducted the largest cross-sectional meta-analysis of the 25(OH)D-pulmonary function association to date, based on nine European ancestry (EA) cohorts (n 22 838) and five African ancestry (AA) cohorts (n 4290) in the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. Data were analysed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean serum 25(OH)D was 68 (SD 29) nmol/l for EA and 49 (SD 21) nmol/l for AA. For each 1 nmol/l higher 25(OH)D, forced expiratory volume in the 1st second (FEV1) was higher by 1.1 ml in EA (95 % CI 0.9, 1.3; P< 0.0001) and 1.8 ml (95 % CI 1.1, 2.5; P< 0.0001) in AA (P-race (difference) = 0.06), and forced vital capacity (FVC) was higher by 1.3 ml in EA (95 % CI 1.0, 1.6; P <0.0001) and 1.5 ml (95 % CI 0.8, 2.3; P= 0.0001) in AA (P-race difference = 0.56). Among EA, the 25(OH)D-FVC association was stronger in smokers: per 1 nmol/l higher 25(OH) D, FVC was higher by 1.7 ml (95 % CI 1.1, 2.3) for current smokers and 1.7 ml (95 % CI 1.2, 2.1) for former smokers, compared with 0.8 ml (95 % CI 0.4, 1.2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EA, a stronger association was observed for smokers compared with never smokers, which supports the importance of vitamin D in vulnerable populations

    Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

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    OBJECTIVE Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations. RESEARCH DESIGN AND METHODS We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. RESULTS We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m2 higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h). CONCLUSIONS Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants
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