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Healthful plant-based dietary patterns, genetic risk of obesity, and cardiovascular risk in the UK biobank study.

Clinical nutrition (Edinburgh, Scotland)

Heianza Y, Zhou T, Sun D, Hu FB, Qi L.
PMID: 34237696
Clin Nutr. 2021 Jul;40(7):4694-4701. doi: 10.1016/j.clnu.2021.06.018. Epub 2021 Jun 24.

BACKGROUND & AIMS: People with a higher genetic risk for obesity are more likely to develop cardiovascular disease (CVD), and healthy plant-based dietary patterns may be associated with decreased risks of obesity and cardiovascular events. We investigated whether adherence...

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Heianza Y, Zhou T, Sun D, et al. Healthful plant-based dietary patterns, genetic risk of obesity, and cardiovascular risk in the UK biobank study. Clin Nutr. 2021;40(7):4694-4701doi: 10.1016/j.clnu.2021.06.018.
Heianza, Y., Zhou, T., Sun, D., Hu, F. B., & Qi, L. (2021). Healthful plant-based dietary patterns, genetic risk of obesity, and cardiovascular risk in the UK biobank study. Clinical nutrition (Edinburgh, Scotland), 40(7), 4694-4701. https://doi.org/10.1016/j.clnu.2021.06.018
Heianza, Yoriko, et al. "Healthful plant-based dietary patterns, genetic risk of obesity, and cardiovascular risk in the UK biobank study." Clinical nutrition (Edinburgh, Scotland) vol. 40,7 (2021): 4694-4701. doi: https://doi.org/10.1016/j.clnu.2021.06.018
Heianza Y, Zhou T, Sun D, Hu FB, Qi L. Healthful plant-based dietary patterns, genetic risk of obesity, and cardiovascular risk in the UK biobank study. Clin Nutr. 2021 Jul;40(7):4694-4701. doi: 10.1016/j.clnu.2021.06.018. Epub 2021 Jun 24. PMID: 34237696; PMCID: PMC8338907.
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A Long Non-coding RNA, .

Frontiers in genetics

Manning AK, Goustin AS, Kleinbrink EL, Thepsuwan P, Cai J, Ju D, Leong A, Udler MS, Brown JB, Goodarzi MO, Rotter JI, Sladek R, Meigs JB, Lipovich L.
PMID: 32754192
Front Genet. 2020 Jul 10;11:615. doi: 10.3389/fgene.2020.00615. eCollection 2020.

AIMS: Causal transcripts at genomic loci associated with type 2 diabetes (T2D) are mostly unknown. The chr8p23.1 variant rs4841132, associated with an insulin-resistant diabetes risk phenotype, lies in the second exon of a long non-coding RNA (lncRNA) gene, METHODS:...

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Manning AK, Goustin AS, Kleinbrink EL, et al. A Long Non-coding RNA, . Front Genet. 2020;11:615doi: 10.3389/fgene.2020.00615.
Manning, A. K., Goustin, A. S., Kleinbrink, E. L., Thepsuwan, P., Cai, J., Ju, D., Leong, A., Udler, M. S., Brown, J. B., Goodarzi, M. O., Rotter, J. I., Sladek, R., Meigs, J. B., & Lipovich, L. (2020). A Long Non-coding RNA, . Frontiers in genetics, 11615. https://doi.org/10.3389/fgene.2020.00615
Manning, Alisa K, et al. "A Long Non-coding RNA, ." Frontiers in genetics vol. 11 (2020): 615. doi: https://doi.org/10.3389/fgene.2020.00615
Manning AK, Goustin AS, Kleinbrink EL, Thepsuwan P, Cai J, Ju D, Leong A, Udler MS, Brown JB, Goodarzi MO, Rotter JI, Sladek R, Meigs JB, Lipovich L. A Long Non-coding RNA, . Front Genet. 2020 Jul 10;11:615. doi: 10.3389/fgene.2020.00615. eCollection 2020. PMID: 32754192; PMCID: PMC7367044.
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Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies.

Gut

Qi Q, Li J, Yu B, Moon JY, Chai JC, Merino J, Hu J, Ruiz-Canela M, Rebholz C, Wang Z, Usyk M, Chen GC, Porneala BC, Wang W, Nguyen NQ, Feofanova EV, Grove ML, Wang TJ, Gerszten RE, Dupuis J, Salas-Salvadó J, Bao W, Perkins DL, Daviglus ML, Thyagarajan B, Cai J, Wang T, Manson JE, Martínez-González MA, Selvin E, Rexrode KM, Clish CB, Hu FB, Meigs JB, Knight R, Burk RD, Boerwinkle E, Kaplan RC.
PMID: 34127525
Gut. 2021 Jun 14; doi: 10.1136/gutjnl-2021-324053. Epub 2021 Jun 14.

OBJECTIVE: Tryptophan can be catabolised to various metabolites through host kynurenine and microbial indole pathways. We aimed to examine relationships of host and microbial tryptophan metabolites with incident type 2 diabetes (T2D), host genetics, diet and gut microbiota.METHOD: We...

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Qi Q, Li J, Yu B, et al. Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies. Gut. 2021;doi: 10.1136/gutjnl-2021-324053.
Qi, Q., Li, J., Yu, B., Moon, J. Y., Chai, J. C., Merino, J., Hu, J., Ruiz-Canela, M., Rebholz, C., Wang, Z., Usyk, M., Chen, G. C., Porneala, B. C., Wang, W., Nguyen, N. Q., Feofanova, E. V., Grove, M. L., Wang, T. J., Gerszten, R. E., Dupuis, J., Salas-Salvadó, J., Bao, W., Perkins, D. L., Daviglus, M. L., Thyagarajan, B., Cai, J., Wang, T., Manson, J. E., Martínez-González, M. A., Selvin, E., Rexrode, K. M., Clish, C. B., Hu, F. B., Meigs, J. B., Knight, R., Burk, R. D., Boerwinkle, E., & Kaplan, R. C. (2021). Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies. Gut, . https://doi.org/10.1136/gutjnl-2021-324053
Qi, Qibin, et al. "Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies." Gut vol. (2021). doi: https://doi.org/10.1136/gutjnl-2021-324053
Qi Q, Li J, Yu B, Moon JY, Chai JC, Merino J, Hu J, Ruiz-Canela M, Rebholz C, Wang Z, Usyk M, Chen GC, Porneala BC, Wang W, Nguyen NQ, Feofanova EV, Grove ML, Wang TJ, Gerszten RE, Dupuis J, Salas-Salvadó J, Bao W, Perkins DL, Daviglus ML, Thyagarajan B, Cai J, Wang T, Manson JE, Martínez-González MA, Selvin E, Rexrode KM, Clish CB, Hu FB, Meigs JB, Knight R, Burk RD, Boerwinkle E, Kaplan RC. Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies. Gut. 2021 Jun 14; doi: 10.1136/gutjnl-2021-324053. Epub 2021 Jun 14. PMID: 34127525; PMCID: PMC8697256.
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Detecting differentially methylated regions with multiple distinct associations.

Epigenomics

Lent S, Cardenas A, Rifas-Shiman SL, Perron P, Bouchard L, Liu CT, Hivert MF, Dupuis J.
PMID: 33641349
Epigenomics. 2021 Mar;13(6):451-464. doi: 10.2217/epi-2020-0344. Epub 2021 Mar 01.

No abstract available.

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Lent S, Cardenas A, Rifas-Shiman SL, et al. Detecting differentially methylated regions with multiple distinct associations. Epigenomics. 2021;13(6):451-464doi: 10.2217/epi-2020-0344.
Lent, S., Cardenas, A., Rifas-Shiman, S. L., Perron, P., Bouchard, L., Liu, C. T., Hivert, M. F., & Dupuis, J. (2021). Detecting differentially methylated regions with multiple distinct associations. Epigenomics, 13(6), 451-464. https://doi.org/10.2217/epi-2020-0344
Lent, Samantha, et al. "Detecting differentially methylated regions with multiple distinct associations." Epigenomics vol. 13,6 (2021): 451-464. doi: https://doi.org/10.2217/epi-2020-0344
Lent S, Cardenas A, Rifas-Shiman SL, Perron P, Bouchard L, Liu CT, Hivert MF, Dupuis J. Detecting differentially methylated regions with multiple distinct associations. Epigenomics. 2021 Mar;13(6):451-464. doi: 10.2217/epi-2020-0344. Epub 2021 Mar 01. PMID: 33641349; PMCID: PMC8023344.
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Six-Year Diabetes Incidence After Genetic Risk Testing and Counseling: A Randomized Clinical Trial.

Diabetes care

Vassy JL, He W, Florez JC, Meigs JB, Grant RW.
PMID: 29305403
Diabetes Care. 2018 Mar;41(3):e25-e26. doi: 10.2337/dc17-1793. Epub 2018 Jan 05.

No abstract available.

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Vassy JL, He W, Florez JC, et al. Six-Year Diabetes Incidence After Genetic Risk Testing and Counseling: A Randomized Clinical Trial. Diabetes Care. 2018;41(3):e25-e26doi: 10.2337/dc17-1793.
Vassy, J. L., He, W., Florez, J. C., Meigs, J. B., & Grant, R. W. (2018). Six-Year Diabetes Incidence After Genetic Risk Testing and Counseling: A Randomized Clinical Trial. Diabetes care, 41(3), e25-e26. https://doi.org/10.2337/dc17-1793
Vassy, Jason L, et al. "Six-Year Diabetes Incidence After Genetic Risk Testing and Counseling: A Randomized Clinical Trial." Diabetes care vol. 41,3 (2018): e25-e26. doi: https://doi.org/10.2337/dc17-1793
Vassy JL, He W, Florez JC, Meigs JB, Grant RW. Six-Year Diabetes Incidence After Genetic Risk Testing and Counseling: A Randomized Clinical Trial. Diabetes Care. 2018 Mar;41(3):e25-e26. doi: 10.2337/dc17-1793. Epub 2018 Jan 05. PMID: 29305403; PMCID: PMC5829962.
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Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach.

Journal of the American Statistical Association

Pham LM, Carvalho L, Schaus S, Kolaczyk ED.
PMID: 27647944
J Am Stat Assoc. 2016;111(513):73-92. doi: 10.1080/01621459.2015.1110523. Epub 2016 May 05.

Cellular response to a perturbation is the result of a dynamic system of biological variables linked in a complex network. A major challenge in drug and disease studies is identifying the key factors of a biological network that are...

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Pham LM, Carvalho L, Schaus S, et al. Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach. J Am Stat Assoc. 2016;111(513):73-92doi: 10.1080/01621459.2015.1110523.
Pham, L. M., Carvalho, L., Schaus, S., & Kolaczyk, E. D. (2016). Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach. Journal of the American Statistical Association, 111(513), 73-92. https://doi.org/10.1080/01621459.2015.1110523
Pham, Lisa M, et al. "Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach." Journal of the American Statistical Association vol. 111,513 (2016): 73-92. doi: https://doi.org/10.1080/01621459.2015.1110523
Pham LM, Carvalho L, Schaus S, Kolaczyk ED. Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach. J Am Stat Assoc. 2016;111(513):73-92. doi: 10.1080/01621459.2015.1110523. Epub 2016 May 05. PMID: 27647944; PMCID: PMC5026418.
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Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease.

Current cardiovascular risk reports

Dauriz M, Meigs JB.
PMID: 24729826
Curr Cardiovasc Risk Rep. 2014 Jan 01;8(1):368. doi: 10.1007/s12170-013-0368-z.

The large-scale genome-wide association studies conducted so far identified numerous allelic variants associated with type 2 diabetes (T2D), coronary heart disease (CHD) and related cardiometabolic traits. Many T2D- and some CHD-risk loci are also linked with metabolic traits that...

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Dauriz M, Meigs JB. Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease. Curr Cardiovasc Risk Rep. 2014;8(1):368doi: 10.1007/s12170-013-0368-z.
Dauriz, M., & Meigs, J. B. (2014). Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease. Current cardiovascular risk reports, 8(1), 368. https://doi.org/10.1007/s12170-013-0368-z
Dauriz, Marco, and Meigs, James B. "Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease." Current cardiovascular risk reports vol. 8,1 (2014): 368. doi: https://doi.org/10.1007/s12170-013-0368-z
Dauriz M, Meigs JB. Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease. Curr Cardiovasc Risk Rep. 2014 Jan 01;8(1):368. doi: 10.1007/s12170-013-0368-z. PMID: 24729826; PMCID: PMC3981553.
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Educational attainment and drinking behaviors: Mendelian randomization study in UK Biobank.

Molecular psychiatry

Zhou T, Sun D, Li X, Ma H, Heianza Y, Qi L.
PMID: 31768000
Mol Psychiatry. 2021 Aug;26(8):4355-4366. doi: 10.1038/s41380-019-0596-9. Epub 2019 Nov 25.

Educational attainment has been associated with drinking behaviors in observation studies. We performed Mendelian randomization analysis to determine whether educational attainment causally affected drinking behaviors, including amount of alcohol intakes (in total and various types), drinking frequency, and drinking...

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Zhou T, Sun D, Li X, et al. Educational attainment and drinking behaviors: Mendelian randomization study in UK Biobank. Mol Psychiatry. 2019;26(8):4355-4366doi: 10.1038/s41380-019-0596-9.
Zhou, T., Sun, D., Li, X., Ma, H., Heianza, Y., & Qi, L. (2021). Educational attainment and drinking behaviors: Mendelian randomization study in UK Biobank. Molecular psychiatry, 26(8), 4355-4366. https://doi.org/10.1038/s41380-019-0596-9
Zhou, Tao, et al. "Educational attainment and drinking behaviors: Mendelian randomization study in UK Biobank." Molecular psychiatry vol. 26,8 (2021): 4355-4366. doi: https://doi.org/10.1038/s41380-019-0596-9
Zhou T, Sun D, Li X, Ma H, Heianza Y, Qi L. Educational attainment and drinking behaviors: Mendelian randomization study in UK Biobank. Mol Psychiatry. 2021 Aug;26(8):4355-4366. doi: 10.1038/s41380-019-0596-9. Epub 2019 Nov 25. PMID: 31768000; PMCID: PMC7246132.
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Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality.

Journal of internal medicine

Zhou T, Yuan Y, Xue Q, Li X, Wang M, Ma H, Heianza Y, Qi L.
PMID: 34237797
J Intern Med. 2022 Jan;291(1):64-71. doi: 10.1111/joim.13367. Epub 2021 Aug 02.

BACKGROUND: Individual unhealthy sleep behaviours have been associated with increased risks of all-cause mortality and deaths due to cardiovascular disease (CVD) or cancer. The evidence regarding the association of sleep patterns with these risks is limited.OBJECTIVE: To examine the...

Cite
Zhou T, Yuan Y, Xue Q, et al. Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality. J Intern Med. 2021;291(1):64-71doi: 10.1111/joim.13367.
Zhou, T., Yuan, Y., Xue, Q., Li, X., Wang, M., Ma, H., Heianza, Y., & Qi, L. (2022). Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality. Journal of internal medicine, 291(1), 64-71. https://doi.org/10.1111/joim.13367
Zhou, Tao, et al. "Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality." Journal of internal medicine vol. 291,1 (2022): 64-71. doi: https://doi.org/10.1111/joim.13367
Zhou T, Yuan Y, Xue Q, Li X, Wang M, Ma H, Heianza Y, Qi L. Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality. J Intern Med. 2022 Jan;291(1):64-71. doi: 10.1111/joim.13367. Epub 2021 Aug 02. PMID: 34237797; PMCID: PMC8688171.
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Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality.

Journal of internal medicine

Zhou T, Yuan Y, Xue Q, Li X, Wang M, Ma H, Heianza Y, Qi L.
PMID: 34237797
J Intern Med. 2022 Jan;291(1):64-71. doi: 10.1111/joim.13367. Epub 2021 Aug 02.

BACKGROUND: Individual unhealthy sleep behaviours have been associated with increased risks of all-cause mortality and deaths due to cardiovascular disease (CVD) or cancer. The evidence regarding the association of sleep patterns with these risks is limited.OBJECTIVE: To examine the...

Cite
Zhou T, Yuan Y, Xue Q, et al. Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality. J Intern Med. 2021;291(1):64-71doi: 10.1111/joim.13367.
Zhou, T., Yuan, Y., Xue, Q., Li, X., Wang, M., Ma, H., Heianza, Y., & Qi, L. (2022). Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality. Journal of internal medicine, 291(1), 64-71. https://doi.org/10.1111/joim.13367
Zhou, Tao, et al. "Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality." Journal of internal medicine vol. 291,1 (2022): 64-71. doi: https://doi.org/10.1111/joim.13367
Zhou T, Yuan Y, Xue Q, Li X, Wang M, Ma H, Heianza Y, Qi L. Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality. J Intern Med. 2022 Jan;291(1):64-71. doi: 10.1111/joim.13367. Epub 2021 Aug 02. PMID: 34237797; PMCID: PMC8688171.
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Showing 1 to 10 of 10 entries