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1. Genome-wide association studies and fine-mapping identify genomic loci for n-3 and n-6 polyunsaturated fatty acids in Hispanic American and African American cohorts

Author

Yang, Chaojie, Veenstra, Jenna, Bartz, Traci M., Pahl, Matthew C., Hallmark, Brian, Chen, Yii-Der Ida, Westra, Jason, Steffen, Lyn M., Brown, Christopher D., Siscovick, David, Tsai, Michael Y., Wood, Alexis C., Rich, Stephen S., Smith, Caren E., O’Connor, Timothy D., Mozaffarian, Dariush, Grant, Struan F. A., Chilton, Floyd H., Tintle, Nathan L., Lemaitre, Rozenn N., and Manichaikul, Ani

Published
2023
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2. Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations.

Author

Haslam, Danielle E, Peloso, Gina M, Guirette, Melanie, Imamura, Fumiaki, Bartz, Traci M, Pitsillides, Achilleas N, Wang, Carol A, Li-Gao, Ruifang, Westra, Jason M, Pitkänen, Niina, Young, Kristin L, Graff, Mariaelisa, Wood, Alexis C, Braun, Kim VE, Luan, Jian'an, Kähönen, Mika, Kiefte-de Jong, Jessica C, Ghanbari, Mohsen, Tintle, Nathan, Lemaitre, Rozenn N, Mook-Kanamori, Dennis O, North, Kari, Helminen, Mika, Mossavar-Rahmani, Yasmin, Snetselaar, Linda, Martin, Lisa W, Viikari, Jorma S, Oddy, Wendy H, Pennell, Craig E, Rosendall, Frits R, Ikram, M Arfan, Uitterlinden, Andre G, Psaty, Bruce M, Mozaffarian, Dariush, Rotter, Jerome I, Taylor, Kent D, Lehtimäki, Terho, Raitakari, Olli T, Livingston, Kara A, Voortman, Trudy, Forouhi, Nita G, Wareham, Nick J, de Mutsert, Renée, Rich, Steven S, Manson, JoAnn E, Mora, Samia, Ridker, Paul M, Merino, Jordi, Meigs, James B, Dashti, Hassan S, Chasman, Daniel I, Lichtenstein, Alice H, Smith, Caren E, Dupuis, Josée, Herman, Mark A, and McKeown, Nicola M

Subjects
Humans, Triglycerides, Polymorphism, Single Nucleotide, Adult, Middle Aged, Female, Male, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Cholesterol, HDL, Meta-Analysis as Topic, Sugar-Sweetened Beverages, carbohydrates, dyslipidemia, epidemiology, genetics, nutrition, sugars, triglyceride, Cardiovascular, Genetics, Human Genome
Abstract

BackgroundChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the CHREBP locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the CHREBP locus and dyslipidemia.MethodsData from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near CHREBP were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.ResultsIn a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; P

Published
2021

3. Genome-wide meta-analysis of macronutrient intake of 91,114 European ancestry participants from the cohorts for heart and aging research in genomic epidemiology consortium

Author

Merino, Jordi, Dashti, Hassan S, Li, Sherly X, Sarnowski, Chloé, Justice, Anne E, Graff, Misa, Papoutsakis, Constantina, Smith, Caren E, Dedoussis, George V, Lemaitre, Rozenn N, Wojczynski, Mary K, Männistö, Satu, Ngwa, Julius S, Kho, Minjung, Ahluwalia, Tarunveer S, Pervjakova, Natalia, Houston, Denise K, Bouchard, Claude, Huang, Tao, Orho-Melander, Marju, Frazier-Wood, Alexis C, Mook-Kanamori, Dennis O, Pérusse, Louis, Pennell, Craig E, de Vries, Paul S, Voortman, Trudy, Li, Olivia, Kanoni, Stavroula, Rose, Lynda M, Lehtimäki, Terho, Zhao, Jing Hua, Feitosa, Mary F, Luan, Jian’an, McKeown, Nicola M, Smith, Jennifer A, Hansen, Torben, Eklund, Niina, Nalls, Mike A, Rankinen, Tuomo, Huang, Jinyan, Hernandez, Dena G, Schulz, Christina-Alexandra, Manichaikul, Ani, Li-Gao, Ruifang, Vohl, Marie-Claude, Wang, Carol A, van Rooij, Frank JA, Shin, Jean, Kalafati, Ioanna P, Day, Felix, Ridker, Paul M, Kähönen, Mika, Siscovick, David S, Langenberg, Claudia, Zhao, Wei, Astrup, Arne, Knekt, Paul, Garcia, Melissa, Rao, DC, Qi, Qibin, Ferrucci, Luigi, Ericson, Ulrika, Blangero, John, Hofman, Albert, Pausova, Zdenka, Mikkilä, Vera, Wareham, Nick J, Kardia, Sharon LR, Pedersen, Oluf, Jula, Antti, Curran, Joanne E, Zillikens, M Carola, Viikari, Jorma S, Forouhi, Nita G, Ordovás, José M, Lieske, John C, Rissanen, Harri, Uitterlinden, André G, Raitakari, Olli T, Kiefte-de Jong, Jessica C, Dupuis, Josée, Rotter, Jerome I, North, Kari E, Scott, Robert A, Province, Michael A, Perola, Markus, Cupples, L Adrienne, Turner, Stephen T, Sørensen, Thorkild IA, Salomaa, Veikko, Liu, Yongmei, Sung, Yun J, Qi, Lu, Bandinelli, Stefania, Rich, Stephen S, de Mutsert, Renée, Tremblay, Angelo, Oddy, Wendy H, Franco, Oscar H, and Paus, Tomas

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Obesity, Human Genome, Genetics, Prevention, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Metabolic and endocrine, Aged, Aging, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Cohort Studies, Energy Intake, Female, Fibroblast Growth Factors, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Genotype, Heart Diseases, Humans, Male, Membrane Proteins, Middle Aged, Nutrients, Polymorphism, Single Nucleotide, Receptors, Retinoic Acid, White People, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Macronutrient intake, the proportion of calories consumed from carbohydrate, fat, and protein, is an important risk factor for metabolic diseases with significant familial aggregation. Previous studies have identified two genetic loci for macronutrient intake, but incomplete coverage of genetic variation and modest sample sizes have hindered the discovery of additional loci. Here, we expanded the genetic landscape of macronutrient intake, identifying 12 suggestively significant loci (P

Published
2019

4. A Genome-Wide Association Study Identifies Blood Disorder–Related Variants Influencing Hemoglobin A1c With Implications for Glycemic Status in U.S. Hispanics/Latinos

Author

Moon, Jee-Young, Louie, Tin L, Jain, Deepti, Sofer, Tamar, Schurmann, Claudia, Below, Jennifer E, Lai, Chao-Qiang, Aviles-Santa, M Larissa, Talavera, Gregory A, Smith, Caren E, Petty, Lauren E, Bottinger, Erwin P, Chen, Yii-Der Ida, Taylor, Kent D, Daviglus, Martha L, Cai, Jianwen, Wang, Tao, Tucker, Katherine L, Ordovás, José M, Hanis, Craig L, Loos, Ruth JF, Schneiderman, Neil, Rotter, Jerome I, Kaplan, Robert C, and Qi, Qibin

Subjects
Biomedical and Clinical Sciences, Health Sciences, Genetics, Diabetes, Rare Diseases, Hematology, Prevention, 2.1 Biological and endogenous factors, Aetiology, Adult, Alleles, Blood Glucose, Diabetes Mellitus, Fasting, Female, Genetic Variation, Genome-Wide Association Study, Glucose Tolerance Test, Glycated Hemoglobin, Hematologic Diseases, Hispanic or Latino, Humans, Hyperglycemia, Male, Middle Aged, Phenotype, Prediabetic State, Prevalence, United States, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences, Health sciences
Abstract

ObjectiveWe aimed to identify hemoglobin A1c (HbA1c)-associated genetic variants and examine their implications for glycemic status evaluated by HbA1c in U.S. Hispanics/Latinos with diverse genetic ancestries.Research design and methodsWe conducted a genome-wide association study (GWAS) of HbA1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies.ResultsOur GWAS and replication analyses showed 10 previously known and novel loci associated with HbA1c at genome-wide significance levels (P < 5.0 × 10-8). In particular, two African ancestry-specific variants, HBB-rs334 and G6PD-rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA1c-associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM-rs145546625, was associated with HbA1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB-rs334 or G6PD-rs1050828 HbA1c-lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA1c level taking HBB-rs334 and G6PD-rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28).ConclusionsThis study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA1c test is performed.

Published
2019

6. Genome‐Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

Author

Smith, Caren E, Follis, Jack L, Dashti, Hassan S, Tanaka, Toshiko, Graff, Mariaelisa, Fretts, Amanda M, Kilpeläinen, Tuomas O, Wojczynski, Mary K, Richardson, Kris, Nalls, Mike A, Schulz, Christina‐Alexandra, Liu, Yongmei, Frazier‐Wood, Alexis C, van Eekelen, Esther, Wang, Carol, de Vries, Paul S, Mikkilä, Vera, Rohde, Rebecca, Psaty, Bruce M, Hansen, Torben, Feitosa, Mary F, Lai, Chao‐Qiang, Houston, Denise K, Ferruci, Luigi, Ericson, Ulrika, Wang, Zhe, de Mutsert, Renée, Oddy, Wendy H, de Jonge, Ester AL, Seppälä, Ilkka, Justice, Anne E, Lemaitre, Rozenn N, Sørensen, Thorkild IA, Province, Michael A, Parnell, Laurence D, Garcia, Melissa E, Bandinelli, Stefania, Orho‐Melander, Marju, Rich, Stephen S, Rosendaal, Frits R, Pennell, Craig E, Jong, Jessica C Kiefte‐de, Kähönen, Mika, Young, Kristin L, Pedersen, Oluf, Aslibekyan, Stella, Rotter, Jerome I, Mook‐Kanamori, Dennis O, Zillikens, M Carola, Raitakari, Olli T, North, Kari E, Overvad, Kim, Arnett, Donna K, Hofman, Albert, Lehtimäki, Terho, Tjønneland, Anne, Uitterlinden, André G, Rivadeneira, Fernando, Franco, Oscar H, German, J Bruce, Siscovick, David S, Cupples, L Adrienne, and Ordovás, José M

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Genetics, Prevention, Nutrition, Obesity, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Cancer, Metabolic and endocrine, Actins, Adult, Aged, Body Mass Index, Cohort Studies, Cross-Sectional Studies, Dairy Products, Female, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Myosin-Light-Chain Phosphatase, Polymorphism, Single Nucleotide, White People, body mass index, CHARGE consortium, dairy intake, genome-wide interaction study, meta-analysis, Food Sciences, Public Health and Health Services, Food Science, Nutrition & Dietetics, Food sciences, Nutrition and dietetics
Abstract

ScopeBody 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 resultsA 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

Published
2018

7. Dairy Consumption and Body Mass Index Among Adults: Mendelian Randomization Analysis of 184802 Individuals from 25 Studies

Author

Huang, Tao, Ding, Ming, Bergholdt Helle, KM, Wang, Tiange, Heianza, Yoriko, Sun, Dianjianyi, Frazier-Wood Alexis, C, Aslibekyan, Stella, North Kari, E, Voortman, Trudy, Graff, Mariaelisa, Smith Caren, E, Lai, Chao-Qiang, Varbo, Anette, Lemaitre, Rozenn N, de Jonge, M Ester AL, Fumeron, Frédéric, Corella, Dolores, Wang, Carol A, Tjønneland, Anne, Overvad, Kim, Sørensen, Thorkild IA, Feitosa, Mary F, Wojczynski, Mary K, Kähönen, Mika, Renström, Frida, Psaty, Bruce M, Siscovick, David S, Barroso, Inês, Johansson, Ingegerd, Hernandez, Dena, Ferrucci, Luigi, Bandinelli, Stefania, Linneberg, Allan, Zillikens, M Carola, Sandholt, Camilla Helene, Pedersen, Oluf, Hansen, Torben, Schulz, Christina-Alexandra, Sonestedt, Emily, Orho-Melander, Marju, Chen, Tzu-An, Rotter, Jerome I, Allison, Mathew A, Rich, Stephen S, Sorlí, Jose V, Coltell, Oscar, Pennell, Craig E, Eastwood, Peter, Hofman, Albert, Uitterlinden, Andre G, van Rooij, Frank JA, Chu, Audrey Y, Rose, Lynda M, Ridker, Paul M, Viikari, Jorma, Raitakari, Olli, Lehtimäki, Terho, Mikkilä, Vera, Willett, Walter C, Wang, Yujie, Tucker, Katherine L, Ordovas, Jose M, Kilpeläinen, Tuomas O, Province, Michael A, Franks, Paul W, Arnett, Donna K, Tanaka, Toshiko, Toft, Ulla, Ericson, Ulrika, Franco, Oscar H, Mozaffarian, Dariush, Hu, Frank B, Chasman, Daniel I, Nordestgaard, Børge G, Ellervik, Christina, and Qi, Lu

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Prevention, Genetics, Adult, Body Mass Index, Body Weight, Cross-Sectional Studies, Dairy Products, Genotype, Humans, Mendelian Randomization Analysis, Polymorphism, Genetic, Polymorphism, Single Nucleotide, Prospective Studies, Mendelian Randomization of Dairy Consumption Working Group, Medical Biotechnology, Medical Biochemistry and Metabolomics, Clinical Sciences, General Clinical Medicine, Clinical sciences, Medical biochemistry and metabolomics
Abstract

BackgroundAssociations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined.MethodsWe performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies.ResultsHigher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00-0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14-0.25) serving/day higher dairy intake (P = 3.15 × 10-12) and 0.12 (95% CI, 0.06-0.17) kg/m2 higher BMI (P = 2.11 × 10-5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27-0.92; P = 3.0 × 10-4).ConclusionsThe present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.

Published
2018

10. Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians 1 , 2

Author

Fretts, Amanda M, Follis, Jack L, Nettleton, Jennifer A, Lemaitre, Rozenn N, Ngwa, Julius S, Wojczynski, Mary K, Kalafati, Ioanna Panagiota, Varga, Tibor V, Frazier-Wood, Alexis C, Houston, Denise K, Lahti, Jari, Ericson, Ulrika, van den Hooven, Edith H, Mikkilä, Vera, Kiefte-de Jong, Jessica C, Mozaffarian, Dariush, Rice, Kenneth, Renström, Frida, North, Kari E, McKeown, Nicola M, Feitosa, Mary F, Kanoni, Stavroula, Smith, Caren E, Garcia, Melissa E, Tiainen, Anna-Maija, Sonestedt, Emily, Manichaikul, Ani, van Rooij, Frank JA, Dimitriou, Maria, Raitakari, Olli, Pankow, James S, Djoussé, Luc, Province, Michael A, Hu, Frank B, Lai, Chao-Qiang, Keller, Margaux F, Perälä, Mia-Maria, Rotter, Jerome I, Hofman, Albert, Graff, Misa, Kähönen, Mika, Mukamal, Kenneth, Johansson, Ingegerd, Ordovas, Jose M, Liu, Yongmei, Männistö, Satu, Uitterlinden, André G, Deloukas, Panos, Seppälä, Ilkka, Psaty, Bruce M, Cupples, L Adrienne, Borecki, Ingrid B, Franks, Paul W, Arnett, Donna K, Nalls, Mike A, Eriksson, Johan G, Orho-Melander, Marju, Franco, Oscar H, Lehtimäki, Terho, Dedoussis, George V, Meigs, James B, and Siscovick, David S

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Prevention, Diabetes, Genetics, Aging, Cardiovascular, Nutrition, Metabolic and endocrine, Blood Glucose, Cohort Studies, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hyperglycemia, Hyperinsulinism, Insulin, Insulin Resistance, Insulin Secretion, Insulin-Secreting Cells, Meat, Meat Products, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, diet, gene–diet interaction, glucose, insulin, meat intake, meta-analysis, Engineering, Medical and Health Sciences, Nutrition & Dietetics, Clinical sciences, Nutrition and dietetics
Abstract

BackgroundRecent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.ObjectiveWe investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.DesignFourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.ResultsProcessed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.ConclusionThe association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Published
2015

12. Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: Meta‐analysis of nine studies in the CHARGE consortium

Author

Smith, Caren E, Follis, Jack L, Nettleton, Jennifer A, Foy, Millennia, Wu, Jason HY, Ma, Yiyi, Tanaka, Toshiko, Manichakul, Ani W, Wu, Hongyu, Chu, Audrey Y, Steffen, Lyn M, Fornage, Myriam, Mozaffarian, Dariush, Kabagambe, Edmond K, Ferruci, Luigi, Chen, Yii-Der Ida, Rich, Stephen S, Djoussé, Luc, Ridker, Paul M, Tang, Weihong, McKnight, Barbara, Tsai, Michael Y, Bandinelli, Stefania, Rotter, Jerome I, Hu, Frank B, Chasman, Daniel I, Psaty, Bruce M, Arnett, Donna K, King, Irena B, Sun, Qi, Wang, Lu, Lumley, Thomas, Chiuve, Stephanie E, Siscovick, David S, Ordovás, José M, and Lemaitre, Rozenn N

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Prevention, Complementary and Integrative Health, Nutrition, Genetics, Acetyltransferases, Acyltransferases, Adaptor Proteins, Signal Transducing, Carboxy-Lyases, Delta-5 Fatty Acid Desaturase, Diet, Docosahexaenoic Acids, Eicosapentaenoic Acid, Erythrocyte Membrane, Fatty Acid Desaturases, Fatty Acid Elongases, Fatty Acids, Fatty Acids, Omega-3, Female, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, FADS1, Gene-diet interactions, Meta-analysis, Omega-3 fatty acids, Food Sciences, Public Health and Health Services, Food Science, Nutrition & Dietetics, Food sciences, Nutrition and dietetics
Abstract

ScopeTissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated interactions between genetic variants and fatty acid intakes for circulating alpha-linoleic acid, eicosapentaenoic acid, docosahexaenoic acid, and docosapentaenoic acid.Methods and resultsWe conducted meta-analyses (N = 11 668) evaluating interactions between dietary fatty acids and genetic variants (rs174538 and rs174548 in FADS1 (fatty acid desaturase 1), rs7435 in AGPAT3 (1-acyl-sn-glycerol-3-phosphate), rs4985167 in PDXDC1 (pyridoxal-dependent decarboxylase domain-containing 1), rs780094 in GCKR (glucokinase regulatory protein), and rs3734398 in ELOVL2 (fatty acid elongase 2)). Stratification by measurement compartment (plasma versus erthyrocyte) revealed compartment-specific interactions between FADS1 rs174538 and rs174548 and dietary alpha-linolenic acid and linoleic acid for docosahexaenoic acid and docosapentaenoic acid.ConclusionOur findings reinforce earlier reports that genetically based differences in circulating fatty acids may be partially due to differences in the conversion of fatty acid precursors. Further, fatty acids measurement compartment may modify gene-diet relationships, and considering compartment may improve the detection of gene-fatty acids interactions for circulating fatty acid outcomes.

Published
2015

13. Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants 2–4

Author

Dashti, Hassan S, Follis, Jack L, Smith, Caren E, Tanaka, Toshiko, Cade, Brian E, Gottlieb, Daniel J, Hruby, Adela, Jacques, Paul F, Lamon-Fava, Stefania, Richardson, Kris, Saxena, Richa, Scheer, Frank AJL, Kovanen, Leena, Bartz, Traci M, Perälä, Mia-Maria, Jonsson, Anna, Frazier-Wood, Alexis C, Kalafati, Ioanna-Panagiota, Mikkilä, Vera, Partonen, Timo, Lemaitre, Rozenn N, Lahti, Jari, Hernandez, Dena G, Toft, Ulla, Johnson, W Craig, Kanoni, Stavroula, Raitakari, Olli T, Perola, Markus, Psaty, Bruce M, Ferrucci, Luigi, Grarup, Niels, Highland, Heather M, Rallidis, Loukianos, Kähönen, Mika, Havulinna, Aki S, Siscovick, David S, Räikkönen, Katri, Jørgensen, Torben, Rotter, Jerome I, Deloukas, Panos, Viikari, Jorma SA, Mozaffarian, Dariush, Linneberg, Allan, Seppälä, Ilkka, Hansen, Torben, Salomaa, Veikko, Gharib, Sina A, Eriksson, Johan G, Bandinelli, Stefania, Pedersen, Oluf, Rich, Stephen S, Dedoussis, George, Lehtimäki, Terho, and Ordovás, José M

Subjects
Aging, Sleep Research, Obesity, Prevention, Nutrition, Genetics, Neurosciences, Behavioral and Social Science, Oral and gastrointestinal, Cardiovascular, Metabolic and endocrine, Cancer, Adult, Body Mass Index, CLOCK Proteins, Cohort Studies, Cross-Sectional Studies, Diet, Dietary Proteins, Energy Intake, Fatty Acids, Unsaturated, Female, Gene-Environment Interaction, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Sleep, White People, Young Adult, CLOCK, circadian rhythm, dietary intake, gene-environment interaction, sleep duration, gene-environment, interaction, Engineering, Medical and Health Sciences, Nutrition & Dietetics
Abstract

BackgroundShort sleep duration has been associated with greater risks of obesity, hypertension, diabetes, and cardiovascular disease. Also, common genetic variants in the human Circadian Locomotor Output Cycles Kaput (CLOCK) show associations with ghrelin and total energy intake.ObjectivesWe examined associations between habitual sleep duration, body mass index (BMI), and macronutrient intake and assessed whether CLOCK variants modify these associations.DesignWe conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations of sleep duration and BMI and macronutrient intake as percentages of total energy as well as interactions with CLOCK variants from 9 cohort studies including up to 14,906 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.ResultsWe observed a significant association between sleep duration and lower BMI (β ± SE = 0.16 ± 0.04, P < 0.0001) in the overall sample; however, associations between sleep duration and relative macronutrient intake were evident in age- and sex-stratified analyses only. We observed a significant association between sleep duration and lower saturated fatty acid intake in younger (aged 20-64 y) adults (men: 0.11 ± 0.06%, P = 0.03; women: 0.10 ± 0.05%, P = 0.04) and with lower carbohydrate (-0.31 ± 0.12%, P < 0.01), higher total fat (0.18 ± 0.09%, P = 0.05), and higher PUFA (0.05 ± 0.02%, P = 0.02) intakes in older (aged 65-80 y) women. In addition, the following 2 nominally significant interactions were observed: between sleep duration and rs12649507 on PUFA intake and between sleep duration and rs6858749 on protein intake.ConclusionsOur results indicate that longer habitual sleep duration is associated with lower BMI and age- and sex-specific favorable dietary behaviors. Differences in the relative intake of specific macronutrients associated with short sleep duration could, at least in part, explain previously reported associations between short sleep duration and chronic metabolic abnormalities. In addition, the influence of obesity-associated CLOCK variants on the association between sleep duration and macronutrient intake suggests that longer habitual sleep duration could ameliorate the genetic predisposition to obesity via a favorable dietary profile.

Published
2015

14. Saturated Fat Intake Modulates the Association between an Obesity Genetic Risk Score and Body Mass Index in Two US Populations

Author

Casas-Agustench, Patricia, Arnett, Donna K, Smith, Caren E, Lai, Chao-Qiang, Parnell, Laurence D, Borecki, Ingrid B, Frazier-Wood, Alexis C, Allison, Matthew, Chen, Yii-Der Ida, Taylor, Kent D, Rich, Stephen S, Rotter, Jerome I, Lee, Yu-Chi, and Ordovás, José M

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Health Sciences, Prevention, Cardiovascular, Nutrition, Genetics, Obesity, Aetiology, 2.3 Psychological, social and economic factors, 2.1 Biological and endogenous factors, Metabolic and endocrine, Oral and gastrointestinal, Cancer, Stroke, Adult, Aged, Body Mass Index, Cross-Sectional Studies, Diet, Dietary Fats, Energy Intake, Fatty Acids, Female, Gene-Environment Interaction, Genetic Predisposition to Disease, Genotype, Humans, Life Style, Linear Models, Male, Middle Aged, Motor Activity, Nutrition Assessment, Risk Factors, United States, White People, Body mass index, Genetic risk score, Saturated fat, Saturated fatty acids, Clinical Sciences, Anthropology, Biomedical and clinical sciences, Health sciences
Abstract

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

Published
2014

15. Dietary and supplemental intake of vitamins C and E is associated with altered DNA methylation in an epigenome-wide association study meta-analysis

Author

Keshawarz, Amena, primary, Joehanes, Roby, additional, Ma, Jiantao, additional, Lee, Gha Young, additional, Costeira, Ricardo, additional, Tsai, Pei-Chien, additional, Masachs, Olatz M., additional, Bell, Jordana T., additional, Wilson, Rory, additional, Thorand, Barbara, additional, Winkelmann, Juliane, additional, Peters, Annette, additional, Linseisen, Jakob, additional, Waldenberger, Melanie, additional, Lehtimäki, Terho, additional, Mishra, Pashupati P., additional, Kähönen, Mika, additional, Raitakari, Olli, additional, Helminen, Mika, additional, Wang, Carol A., additional, Melton, Phillip E., additional, Huang, Rae-Chi, additional, Pennell, Craig E., additional, O’Sullivan, Therese A., additional, Ochoa-Rosales, Carolina, additional, Voortman, Trudy, additional, van Meurs, Joyce B.J., additional, Young, Kristin L., additional, Graff, Misa, additional, Wang, Yujie, additional, Kiel, Douglas P., additional, Smith, Caren E., additional, Jacques, Paul F., additional, and Levy, Daniel, additional

Published
2023
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19. Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis

Author

McKeown, Nicola M., Dashti, Hassan S., Ma, Jiantao, Haslam, Danielle E., Kiefte-de Jong, Jessica C., Smith, Caren E., Tanaka, Toshiko, Graff, Mariaelisa, Lemaitre, Rozenn N., Rybin, Denis, Sonestedt, Emily, Frazier-Wood, Alexis C., Mook-Kanamori, Dennis O., Li, Yanping, Wang, Carol A., Leermakers, Elisabeth T. M., Mikkilä, Vera, Young, Kristin L., Mukamal, Kenneth J., Cupples, L. Adrienne, Schulz, Christina-Alexandra, Chen, Tzu-An, Li-Gao, Ruifang, Huang, Tao, Oddy, Wendy H., Raitakari, Olli, Rice, Kenneth, Meigs, James B., Ericson, Ulrika, Steffen, Lyn M., Rosendaal, Frits R., Hofman, Albert, Kähönen, Mika, Psaty, Bruce M., Brunkwall, Louise, Uitterlinden, Andre G., Viikari, Jorma, Siscovick, David S., Seppälä, Ilkka, North, Kari E., Mozaffarian, Dariush, Dupuis, Josée, Orho-Melander, Marju, Rich, Stephen S., de Mutsert, Renée, Qi, Lu, Pennell, Craig E., Franco, Oscar H., Lehtimäki, Terho, and Herman, Mark A.

Published
2018
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22. Interaction of methylation-related genetic variants with circulating fatty acids on plasma lipids: a meta-analysis of 7 studies and methylation analysis of 3 studies in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium

Author

Ma, Yiyi, Follis, Jack L, Smith, Caren E, Tanaka, Toshiko, Manichaikul, Ani W, Chu, Audrey Y, Samieri, Cecilia, Zhou, Xia, Guan, Weihua, Wang, Lu, Biggs, Mary L, Chen, Yii-Der I, Hernandez, Dena G, Borecki, Ingrid, Chasman, Daniel I, Rich, Stephen S, Ferrucci, Luigi, Irvin, Marguerite Ryan, Aslibekyan, Stella, Zhi, Degui, Tiwari, Hemant K, Claas, Steven A, Sha, Jin, Kabagambe, Edmond K, Lai, Chao-Qiang, Parnell, Laurence D, Lee, Yu-Chi, Amouyel, Philippe, Lambert, Jean-Charles, Psaty, Bruce M, King, Irena B, Mozaffarian, Dariush, McKnight, Barbara, Bandinelli, Stefania, Tsai, Michael Y, Ridker, Paul M, Ding, Jingzhong, Mstat, Kurt Lohmant, Liu, Yongmei, Sotoodehnia, Nona, Barberger-Gateau, Pascale, Steffen, Lyn M, Siscovick, David S, Absher, Devin, Arnett, Donna K, Ordovás, José M, and Lemaitre, Rozenn N

Published
2016
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24. Sugar-Sweetened Beverage Consumption and Plasma Lipoprotein Cholesterol, Apolipoprotein, and Lipoprotein Particle Size Concentrations in US Adults

Author

Haslam, Danielle E, primary, Chasman, Daniel I, additional, Peloso, Gina M, additional, Herman, Mark A, additional, Dupuis, Josée, additional, Lichtenstein, Alice H, additional, Smith, Caren E, additional, Ridker, Paul M, additional, Jacques, Paul F, additional, Mora, Samia, additional, and McKeown, Nicola M, additional

Published
2022
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32. Healthy Aging—Nutrition Matters: Start Early and Screen Often

Author

Roberts, Susan B, primary, Silver, Rachel E, additional, Das, Sai Krupa, additional, Fielding, Roger A, additional, Gilhooly, Cheryl H, additional, Jacques, Paul F, additional, Kelly, Jennifer M, additional, Mason, Joel B, additional, McKeown, Nicola M, additional, Reardon, Meaghan A, additional, Rowan, Sheldon, additional, Saltzman, Edward, additional, Shukitt-Hale, Barbara, additional, Smith, Caren E, additional, Taylor, Allen A, additional, Wu, Dayong, additional, Zhang, Fang Fang, additional, Panetta, Karen, additional, and Booth, Sarah, additional

Published
2021
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34. Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry

Author

Nettleton, Jennifer A., Follis, Jack L., Ngwa, Julius S., Smith, Caren E., Ahmad, Shafqat, Tanaka, Toshiko, Wojczynski, Mary K., Voortman, Trudy, Lemaitre, Rozenn N., Kristiansson, Kati, Nuotio, Marja-Liisa, Houston, Denise K., Perälä, Mia-Maria, Qi, Qibin, Sonestedt, Emily, Manichaikul, Ani, Kanoni, Stavroula, Ganna, Andrea, Mikkilä, Vera, North, Kari E., Siscovick, David S., Harald, Kennet, Mckeown, Nicola M., Johansson, Ingegerd, Rissanen, Harri, Liu, Yongmei, Lahti, Jari, Hu, Frank B., Bandinelli, Stefania, Rukh, Gull, Rich, Stephen, Booij, Lisanne, Dmitriou, Maria, Ax, Erika, Raitakari, Olli, Mukamal, Kenneth, Männistö, Satu, Hallmans, Göran, Jula, Antti, Ericson, Ulrika, Jacobs, David R., Jr, Van Rooij, Frank J. A., Deloukas, Panos, Sjögren, Per, Kähönen, Mika, Djousse, Luc, Perola, Markus, Barroso, Inês, Hofman, Albert, Stirrups, Kathleen, Viikari, Jorma, Uitterlinden, André G., Kalafati, Ioanna P., Franco, Oscar H., Mozaffarian, Dariush, Salomaa, Veikko, Borecki, Ingrid B., Knekt, Paul, Kritchevsky, Stephen B., Eriksson, Johan G., Dedoussis, George V., Qi, Lu, Ferrucci, Luigi, Orho-Melander, Marju, Zillikens, M. Carola, Ingelsson, Erik, Lehtimäki, Terho, Renström, Frida, Cupples, L. Adrienne, Loos, Ruth J. F., and Franks, Paul W.

Published
2015
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35. Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

Author

Dashti, Hassan S., Follis, Jack L., Smith, Caren E., Tanaka, Toshiko, Garaulet, Marta, Gottlieb, Daniel J., Hruby, Adela, Jacques, Paul F., Kiefte-de Jong, Jessica C., Lamon-Fava, Stefania, Scheer, Frank A.J.L., Bartz, Traci M., Kovanen, Leena, Wojczynski, Mary K., Frazier-Wood, Alexis C., Ahluwalia, Tarunveer S., Perälä, Mia-Maria, Jonsson, Anna, Muka, Taulant, Kalafati, Ioanna P., Mikkilä, Vera, and Ordovás, José M.

Published
2015
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37. Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants1-5

Author

Dashti, Hassan S, Follis, Jack L, Smith, Caren E, Tanaka, Toshiko, Cade, Brian E, Gottlieb, Daniel J, Hruby, Adela, Jacques, Paul F, Lamon-Fava, Stefania, Richardson, Kris, Saxena, Richa, Scheer, Frank AJL, Kovanen, Leena, Bartz, Traci M, Perälä, Mia-Maria, Jonsson, Anna, Frazier-Wood, Alexis C, Kalafati, Ioanna-Panagiota, Mikkilä, Vera, Partonen, Timo, Lemaitre, Rozenn N, Lahti, Jari, Hernandez, Dena G, Toft, Ulla, Johnson, Craig W, Kanoni, Stavroula, Raitakari, Olli T, Perola, Markus, Psaty, Bruce M, Ferrucci, Luigi, Grarup, Niels, Highland, Heather M, Rallidis, Loukianos, Kähönen, Mika, Havulinna, Aki S, Siscovick, David S, Räikkönen, Katri, Jørgensen, Torben, Rotter, Jerome I, Deloukas, Panos, Viikari, Jorma SA, Mozaffarian, Dariush, Linneberg, Allan, Seppälä, Ilkka, Hansen, Torben, Salomaa, Veikko, Gharib, Sina A, Eriksson, Johan G, Bandinelli, Stefania, Pedersen, Oluf, Rich, Stephen S, Dedoussis, George, Lehtimäki, Terho, and Ordovás, José M

Published
2015
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38. FTO genetic variants, dietary intake and body mass index: insights from 177 330 individuals

Author

Qi, Qibin, Kilpeläinen, Tuomas O., Downer, Mary K., Tanaka, Toshiko, Smith, Caren E., Sluijs, Ivonne, Sonestedt, Emily, Chu, Audrey Y., Renström, Frida, Lin, Xiaochen, Ängquist, Lars H., Huang, Jinyan, Liu, Zhonghua, Li, Yanping, Asif Ali, Muhammad, Xu, Min, Ahluwalia, Tarunveer Singh, Boer, Jolanda M.A., Chen, Peng, Daimon, Makoto, Eriksson, Johan, Perola, Markus, Friedlander, Yechiel, Gao, Yu-Tang, Heppe, Denise H.M., Holloway, John W., Houston, Denise K., Kanoni, Stavroula, Kim, Yu-Mi, Laaksonen, Maarit A., Jääskeläinen, Tiina, Lee, Nanette R., Lehtimäki, Terho, Lemaitre, Rozenn N., Lu, Wei, Luben, Robert N., Manichaikul, Ani, Männistö, Satu, Marques-Vidal, Pedro, Monda, Keri L., Ngwa, Julius S., Perusse, Louis, van Rooij, Frank J.A., Xiang, Yong-Bing, Wen, Wanqing, Wojczynski, Mary K, Zhu, Jingwen, Borecki, Ingrid B., Bouchard, Claude, Cai, Qiuyin, Cooper, Cyrus, Dedoussis, George V., Deloukas, Panos, Ferrucci, Luigi, Forouhi, Nita G., Hansen, Torben, Christiansen, Lene, Hofman, Albert, Johansson, Ingegerd, Jørgensen, Torben, Karasawa, Shigeru, Khaw, Kay-Tee, Kim, Mi-Kyung, Kristiansson, Kati, Li, Huaixing, Lin, Xu, Liu, Yongmei, Lohman, Kurt K., Long, Jirong, Mikkilä, Vera, Mozaffarian, Dariush, North, Kari, Pedersen, Oluf, Raitakari, Olli, Rissanen, Harri, Tuomilehto, Jaakko, van der Schouw, Yvonne T., Uitterlinden, André G., Zillikens, M. Carola, Franco, Oscar H., Shyong Tai, E., Ou Shu, Xiao, Siscovick, David S., Toft, Ulla, Verschuren, W.M. Monique, Vollenweider, Peter, Wareham, Nicholas J., Witteman, Jacqueline C.M., Zheng, Wei, Ridker, Paul M., Kang, Jae H., Liang, Liming, Jensen, Majken K., Curhan, Gary C., Pasquale, Louis R., Hunter, David J., Mohlke, Karen L., Uusitupa, Matti, Cupples, L. Adrienne, Rankinen, Tuomo, Orho-Melander, Marju, Wang, Tao, Chasman, Daniel I., Franks, Paul W., Sørensen, Thorkild I.A., Hu, Frank B., Loos, Ruth J. F., Nettleton, Jennifer A., and Qi, Lu

Published
2014
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42. Modulation by dietary fat and carbohydrate of IRS1 association with type 2 diabetes traits in two populations of different ancestries

Author

Zheng, Ju-Sheng, Arnett, Donna K., Parnell, Laurence D., Smith, Caren E., Li, Duo, Borecki, Ingrid B., Tucker, Katherine K., Ordovas, Jose M., and Lai, Chao-qiang

Subjects
Olympus America Inc., Cholesterol -- Analysis, Genomics -- Analysis, Genetic research -- Analysis, Dietary fat -- Analysis, Insulin resistance -- Diet therapy -- Diagnosis -- Analysis, Photographic industry -- Analysis, Type 2 diabetes -- Diet therapy -- Diagnosis -- Analysis, Health
Abstract

OBJECTIVE--Insulin receptor substrate 1 (IRS1) is central to insulin signaling pathways. This study aimed to examine the association of IRS1 variants with insulin resistance (IR) and related phenotypes, as well [...]

Published
2013
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43. Perilipin polymorphism interacts with dietary carbohydrates to modulate anthropometric traits in Hispanics of Caribbean origin

Author

Smith, Caren E., Tucker, Katherine L., Yiannakouris, Nikos, Garcia-Bailo, Bibiana, Mattei, Josiemer, Lai, Chao-Qiang, Parnell, Laurence D., and Ordovas, Jose M.

Subjects
Cellular proteins -- Genetic aspects, Carbohydrates -- Physiological aspects, Lipids -- Properties, Lipids -- Health aspects, Obesity -- Risk factors, Obesity -- Genetic aspects, Hispanic Americans -- Genetic aspects, Hispanic Americans -- Health aspects, Genetic polymorphisms -- Health aspects, Food/cooking/nutrition
Abstract

Perilipin (PLIN) is the major protein surrounding lipid droplets in adipocytes and regulates adipocyte metabolism by modulating the interaction between lipases and triacylglycerol stores. Associations between PLIN gene polymorphisms and obesity risk have been described, but interactions with dietary macronutrients require further attention. We examined whether dietary macronutrients (e.g. carbohydrates and fats) modulated the associations of the common PLIN 11482G > A (rs894160) single nucleotide polymorphism with obesity. We studied a population-based sample of Caribbean-origin Hispanics (n = 920, aged 45-74 y) living in the Boston area. Obesity measures (waist and hip circumference, BMI) did not differ between GG subjects and carriers of the A allele (GA and AA). In multivariate linear regression models, we found a significant interaction between complex carbohydrate intake as a continuous variable and PLIN 11482 G > A genotype for waist circumference (P = 0.002). By dichotomizing complex carbohydrate intake, we found significantly different effects across PLIN 11482G > A genotypes. When complex carbohydrate intake was < 144 g/d, waist circumference was larger in PLIN 11482G > A carriers (P = 0.024). Conversely, when complex carbohydrate intake was [greater than or equal to] 144 g/d, waist and hip circumferences were less in PLIN 11482G > A carriers (P < 0.05). These interactions were not found for simple sugars or total carbohydrates. We identified a significant gene-diet interaction associated with obesity at the PLIN locus. In subjects with higher complex carbohydrate intake, the minor allele was protective against obesity, whereas in subjects with lower carbohydrate intake, the minor allele was associated with increased obesity. These interactions may be relevant to dietary management of obesity.

Published
2008

44. Carbohydrate and fat intake associated with risk of metabolic diseases through epigenetics of CPT1A

Author

Lai, Chao-Qiang, primary, Parnell, Laurence D, additional, Smith, Caren E, additional, Guo, Tao, additional, Sayols-Baixeras, Sergi, additional, Aslibekyan, Stella, additional, Tiwari, Hemant K, additional, Irvin, Marguerite R, additional, Bender, Carl, additional, Fei, David, additional, Hidalgo, Bertha, additional, Hopkins, Paul N, additional, Absher, Devin M, additional, Province, Michael A, additional, Elosua, Roberto, additional, Arnett, Donna K, additional, and Ordovas, Jose M, additional

Published
2020
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