@article {6844, title = {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.}, journal = {Am J Clin Nutr}, volume = {102}, year = {2015}, month = {2015 Nov}, pages = {1266-78}, abstract = {

BACKGROUND: Recent 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.

OBJECTIVE: We 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.

DESIGN: Fourteen 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.

RESULTS: Processed 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.

CONCLUSION: The 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).

}, keywords = {Blood Glucose, Cohort Studies, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hyperglycemia, Hyperinsulinism, Insulin, Insulin Resistance, Insulin-Secreting Cells, Meat, Meat Products, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1938-3207}, doi = {10.3945/ajcn.114.101238}, author = {Fretts, Amanda M and Follis, Jack L and Nettleton, Jennifer A and Lemaitre, Rozenn N and Ngwa, Julius S and Wojczynski, Mary K and Kalafati, Ioanna Panagiota and Varga, Tibor V and Frazier-Wood, Alexis C and Houston, Denise K and Lahti, Jari and Ericson, Ulrika and van den Hooven, Edith H and Mikkil{\"a}, Vera and Kiefte-de Jong, Jessica C and Mozaffarian, Dariush and Rice, Kenneth and Renstrom, Frida and North, Kari E and McKeown, Nicola M and Feitosa, Mary F and Kanoni, Stavroula and Smith, Caren E and Garcia, Melissa E and Tiainen, Anna-Maija and Sonestedt, Emily and Manichaikul, Ani and van Rooij, Frank J A and Dimitriou, Maria and Raitakari, Olli and Pankow, James S and Djouss{\'e}, Luc and Province, Michael A and Hu, Frank B and Lai, Chao-Qiang and Keller, Margaux F and Per{\"a}l{\"a}, Mia-Maria and Rotter, Jerome I and Hofman, Albert and Graff, Misa and K{\"a}h{\"o}nen, Mika and Mukamal, Kenneth and Johansson, Ingegerd and Ordovas, Jose M and Liu, Yongmei and M{\"a}nnist{\"o}, Satu and Uitterlinden, Andr{\'e} G and Deloukas, Panos and Sepp{\"a}l{\"a}, Ilkka and Psaty, Bruce M and Cupples, L Adrienne and Borecki, Ingrid B and Franks, Paul W and Arnett, Donna K and Nalls, Mike A and Eriksson, Johan G and Orho-Melander, Marju and Franco, Oscar H and Lehtim{\"a}ki, Terho and Dedoussis, George V and Meigs, James B and Siscovick, David S} } @article {6951, title = {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.}, journal = {Am J Clin Nutr}, volume = {103}, year = {2016}, month = {2016 Feb}, pages = {567-78}, abstract = {

BACKGROUND: DNA methylation is influenced by diet and single nucleotide polymorphisms (SNPs), and methylation modulates gene expression.

OBJECTIVE: We aimed to explore whether the gene-by-diet interactions on blood lipids act through DNA methylation.

DESIGN: We selected 7 SNPs on the basis of predicted relations in fatty acids, methylation, and lipids. We conducted a meta-analysis and a methylation and mediation analysis with the use of data from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium and the ENCODE (Encyclopedia of DNA Elements) consortium.

RESULTS: On the basis of the meta-analysis of 7 cohorts in the CHARGE consortium, higher plasma HDL cholesterol was associated with fewer C alleles at ATP-binding cassette subfamily A member 1 (ABCA1) rs2246293 (β = -0.6 mg/dL, P = 0.015) and higher circulating eicosapentaenoic acid (EPA) (β = 3.87 mg/dL, P = 5.62 {\texttimes} 10(21)). The difference in HDL cholesterol associated with higher circulating EPA was dependent on genotypes at rs2246293, and it was greater for each additional C allele (β = 1.69 mg/dL, P = 0.006). In the GOLDN (Genetics of Lipid Lowering Drugs and Diet Network) study, higher ABCA1 promoter cg14019050 methylation was associated with more C alleles at rs2246293 (β = 8.84\%, P = 3.51 {\texttimes} 10(18)) and lower circulating EPA (β = -1.46\%, P = 0.009), and the mean difference in methylation of cg14019050 that was associated with higher EPA was smaller with each additional C allele of rs2246293 (β = -2.83\%, P = 0.007). Higher ABCA1 cg14019050 methylation was correlated with lower ABCA1 expression (r = -0.61, P = 0.009) in the ENCODE consortium and lower plasma HDL cholesterol in the GOLDN study (r = -0.12, P = 0.0002). An additional mediation analysis was meta-analyzed across the GOLDN study, Cardiovascular Health Study, and the Multi-Ethnic Study of Atherosclerosis. Compared with the model without the adjustment of cg14019050 methylation, the model with such adjustment provided smaller estimates of the mean plasma HDL cholesterol concentration in association with both the rs2246293 C allele and EPA and a smaller difference by rs2246293 genotypes in the EPA-associated HDL cholesterol. However, the differences between 2 nested models were NS (P > 0.05).

CONCLUSION: We obtained little evidence that the gene-by-fatty acid interactions on blood lipids act through DNA methylation.

}, keywords = {Apolipoproteins E, ATP Binding Cassette Transporter 1, Cholesterol, HDL, Cohort Studies, Diet, DNA Methylation, Eicosapentaenoic Acid, Epigenesis, Genetic, Fatty Acids, Gene Expression Regulation, Humans, Lipids, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Triglycerides}, issn = {1938-3207}, doi = {10.3945/ajcn.115.112987}, author = {Ma, Yiyi and Follis, Jack L and Smith, Caren E and Tanaka, Toshiko and Manichaikul, Ani W and Chu, Audrey Y and Samieri, Cecilia and Zhou, Xia and Guan, Weihua and Wang, Lu and Biggs, Mary L and Chen, Yii-der I and Hernandez, Dena G and Borecki, Ingrid and Chasman, Daniel I and Rich, Stephen S and Ferrucci, Luigi and Irvin, Marguerite Ryan and Aslibekyan, Stella and Zhi, Degui and Tiwari, Hemant K and Claas, Steven A and Sha, Jin and Kabagambe, Edmond K and Lai, Chao-Qiang and Parnell, Laurence D and Lee, Yu-Chi and Amouyel, Philippe and Lambert, Jean-Charles and Psaty, Bruce M and King, Irena B and Mozaffarian, Dariush and McKnight, Barbara and Bandinelli, Stefania and Tsai, Michael Y and Ridker, Paul M and Ding, Jingzhong and Mstat, Kurt Lohmant and Liu, Yongmei and Sotoodehnia, Nona and Barberger-Gateau, Pascale and Steffen, Lyn M and Siscovick, David S and Absher, Devin and Arnett, Donna K and Ordovas, Jose M and Lemaitre, Rozenn N} } @article {7588, title = {Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent.}, journal = {Mol Nutr Food Res}, year = {2017}, month = {2017 Sep 21}, abstract = {

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 <10-7) , 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{\textquoteright} of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 {\texttimes} 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.

}, issn = {1613-4133}, doi = {10.1002/mnfr.201700347}, author = {Smith, Caren E and Follis, Jack L and Dashti, Hassan S and Tanaka, Toshiko and Graff, Mariaelisa and Fretts, Amanda M and Kilpel{\"a}inen, Tuomas O and Wojczynski, Mary K and Richardson, Kris and Nalls, Mike A and Schulz, Christina-Alexandra and Liu, Yongmei and Frazier-Wood, Alexis C and van Eekelen, Esther and Wang, Carol and de Vries, Paul S and Mikkil{\"a}, Vera and Rohde, Rebecca and Psaty, Bruce M and Hansen, Torben and Feitosa, Mary F and Lai, Chao-Qiang and Houston, Denise K and Ferruci, Luigi and Ericson, Ulrika and Wang, Zhe and de Mutsert, Ren{\'e}e and Oddy, Wendy H and de Jonge, Ester A L and Sepp{\"a}l{\"a}, Ilkka and Justice, Anne E and Lemaitre, Rozenn N and S{\o}rensen, Thorkild I A and Province, Michael A and Parnell, Laurence D and Garcia, Melissa E and Bandinelli, Stefania and Orho-Melander, Marju and Rich, Stephen S and Rosendaal, Frits R and Pennell, Craig E and Kiefte-de Jong, Jessica C and K{\"a}h{\"o}nen, Mika and Young, Kristin L and Pedersen, Oluf and Aslibekyan, Stella and Rotter, Jerome I and Mook-Kanamori, Dennis O and Zillikens, M Carola and Raitakari, Olli T and North, Kari E and Overvad, Kim and Arnett, Donna K and Hofman, Albert and Lehtim{\"a}ki, Terho and Tj{\o}nneland, Anne and Uitterlinden, Andr{\'e} G and Rivadeneira, Fernando and Franco, Oscar H and German, J Bruce and Siscovick, David S and Cupples, L Adrienne and Ordovas, Jose M} } @article {8410, title = {Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood.}, journal = {Eur J Epidemiol}, volume = {35}, year = {2020}, month = {2020 Jul}, pages = {685-697}, abstract = {

Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95\% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95\% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = - 0.76, 95\% CI - 2.45 to 1.08~mmHg), 0.06~mmHg lower diastolic blood pressure (β = - 0.06, 95\% CI - 0.93 to 0.87~mmHg), or pulse pressure (β = - 0.65, 95\% CI - 1.38 to 0.69~mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.

}, issn = {1573-7284}, doi = {10.1007/s10654-020-00638-z}, author = {Zheng, Yan and Huang, Tao and Wang, Tiange and Mei, Zhendong and Sun, Zhonghan and Zhang, Tao and Ellervik, Christina and Chai, Jin-Fang and Sim, Xueling and van Dam, Rob M and Tai, E-Shyong and Koh, Woon-Puay and Dorajoo, Rajkumar and Saw, Seang-Mei and Sabanayagam, Charumathi and Wong, Tien Yin and Gupta, Preeti and Rossing, Peter and Ahluwalia, Tarunveer S and Vinding, Rebecca K and Bisgaard, Hans and B{\o}nnelykke, Klaus and Wang, Yujie and Graff, Mariaelisa and Voortman, Trudy and van Rooij, Frank J A and Hofman, Albert and van Heemst, Diana and Noordam, Raymond and Estampador, Angela C and Varga, Tibor V and Enzenbach, Cornelia and Scholz, Markus and Thiery, Joachim and Burkhardt, Ralph and Orho-Melander, Marju and Schulz, Christina-Alexandra and Ericson, Ulrika and Sonestedt, Emily and Kubo, Michiaki and Akiyama, Masato and Zhou, Ang and Kilpel{\"a}inen, Tuomas O and Hansen, Torben and Kleber, Marcus E and Delgado, Graciela and McCarthy, Mark and Lemaitre, Rozenn N and Felix, Janine F and Jaddoe, Vincent W V and Wu, Ying and Mohlke, Karen L and Lehtim{\"a}ki, Terho and Wang, Carol A and Pennell, Craig E and Schunkert, Heribert and Kessler, Thorsten and Zeng, Lingyao and Willenborg, Christina and Peters, Annette and Lieb, Wolfgang and Grote, Veit and Rzehak, Peter and Koletzko, Berthold and Erdmann, Jeanette and Munz, Matthias and Wu, Tangchun and He, Meian and Yu, Caizheng and Lecoeur, C{\'e}cile and Froguel, Philippe and Corella, Dolores and Moreno, Luis A and Lai, Chao-Qiang and Pitk{\"a}nen, Niina and Boreham, Colin A and Ridker, Paul M and Rosendaal, Frits R and de Mutsert, Ren{\'e}e and Power, Chris and Paternoster, Lavinia and S{\o}rensen, Thorkild I A and Tj{\o}nneland, Anne and Overvad, Kim and Djouss{\'e}, Luc and Rivadeneira, Fernando and Lee, Nanette R and Raitakari, Olli T and K{\"a}h{\"o}nen, Mika and Viikari, Jorma and Langhendries, Jean-Paul and Escribano, Joaquin and Verduci, Elvira and Dedoussis, George and K{\"o}nig, Inke and Balkau, Beverley and Coltell, Oscar and Dallongeville, Jean and Meirhaeghe, Aline and Amouyel, Philippe and Gottrand, Fr{\'e}d{\'e}ric and Pahkala, Katja and Niinikoski, Harri and Hypp{\"o}nen, Elina and M{\"a}rz, Winfried and Mackey, David A and Gruszfeld, Dariusz and Tucker, Katherine L and Fumeron, Fr{\'e}d{\'e}ric and Estruch, Ramon and Ordovas, Jose M and Arnett, Donna K and Mook-Kanamori, Dennis O and Mozaffarian, Dariush and Psaty, Bruce M and North, Kari E and Chasman, Daniel I and Qi, Lu} }