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1. Genetic insights into resting heart rate and its role in cardiovascular disease.

Author

van de Vegte, Yordi, Eppinga, Ruben, van der Ende, M, Hagemeijer, Yanick, Mahendran, Yuvaraj, Salfati, Elias, Smith, Albert, Tan, Vanessa, Arking, Dan, Ntalla, Ioanna, Appel, Emil, Schurmann, Claudia, Brody, Jennifer, Rueedi, Rico, Polasek, Ozren, Sveinbjornsson, Gardar, Lecoeur, Cecile, Ladenvall, Claes, Zhao, Jing, Isaacs, Aaron, Wang, Lihua, Luan, Jianan, Hwang, Shih-Jen, Mononen, Nina, Auro, Kirsi, Jackson, Anne, Bielak, Lawrence, Zeng, Linyao, Shah, Nabi, Nethander, Maria, Campbell, Archie, Rankinen, Tuomo, Pechlivanis, Sonali, Qi, Lu, Zhao, Wei, Rizzi, Federica, Tanaka, Toshiko, Robino, Antonietta, Cocca, Massimiliano, Lange, Leslie, Müller-Nurasyid, Martina, Roselli, Carolina, Zhang, Weihua, Kleber, Marcus, Guo, Xiuqing, Lin, Henry, Pavani, Francesca, Galesloot, Tessel, Noordam, Raymond, Milaneschi, Yuri, Schraut, Katharina, den Hoed, Marcel, Degenhardt, Frauke, Trompet, Stella, van den Berg, Marten, Pistis, Giorgio, Tham, Yih-Chung, Weiss, Stefan, Sim, Xueling, Li, Hengtong, van der Most, Peter, Nolte, Ilja, Lyytikäinen, Leo-Pekka, Said, M, Witte, Daniel, Iribarren, Carlos, Launer, Lenore, Ring, Susan, de Vries, Paul, Sever, Peter, Linneberg, Allan, Bottinger, Erwin, Padmanabhan, Sandosh, Psaty, Bruce, Sotoodehnia, Nona, Kolcic, Ivana, Arnar, David, Gudbjartsson, Daniel, Holm, Hilma, Balkau, Beverley, Silva, Claudia, Newton-Cheh, Christopher, Nikus, Kjell, Salo, Perttu, Mohlke, Karen, Peyser, Patricia, Schunkert, Heribert, Lorentzon, Mattias, Lahti, Jari, Rao, Dabeeru, Cornelis, Marilyn, Faul, Jessica, Smith, Jennifer, Stolarz-Skrzypek, Katarzyna, Bandinelli, Stefania, Concas, Maria, Sinagra, Gianfranco, Meitinger, Thomas, Waldenberger, Melanie, and Sinner, Moritz

Subjects
Humans, Cardiovascular Diseases, Risk Factors, Heart Rate, Genetic Predisposition to Disease, Atrial Fibrillation, Mendelian Randomization Analysis, Genome-Wide Association Study, Polymorphism, Single Nucleotide
Abstract

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

Published
2023

3. The mitochondrial multi-omic response to exercise training across rat tissues

Author

Adkins, Joshua N., Armenteros, Jose Juan Almagro, Amper, Mary Anne S., Bae, Dam, Bamman, Marcas, Bararpour, Nasim, Barnes, Jerry, Bergman, Bryan C., Bessesen, Daniel H., Broskey, Nicholas T., Buford, Thomas W., Carr, Steven, Chambers, Toby L., Chavez, Clarisa, Chiu, Roxanne, Clark, Natalie, Cutter, Gary, Evans, Charles R., Franczak, Edziu, Gagne, Nicole, Ge, Yongchao, Hennig, Krista M., Houmard, Joseph A., Huffman, Kim M., Hung, Chia-Jui, Hutchinson-Bunch, Chelsea, Ilkayeva, Olga, Jackson, Bailey E., Jankowski, Catherine M., Jin, Christopher A., Johannsen, Neil M., Katz, Daniel H., Keshishian, Hasmik, Kohrt, Wendy M., Kramer, Kyle S., Kraus, William E., Lester, Bridget, Li, Jun Z., Lira, Ana K., Lowe, Adam, Mani, D.R., Many, Gina M., May, Sandy, Melanson, Edward L., Moore, Samuel G., Moreau, Kerrie L., Musi, Nicolas, Nachun, Daniel, Nair, Venugopalan D., Newgard, Christopher, Nudelman, German, Piehowski, Paul D., Pincas, Hanna, Qian, Wei-Jun, Rankinen, Tuomo, Rasmussen, Blake B., Ravussin, Eric, Rooney, Jessica L., Rushing, Scott, Samdarshi, Mihir, Sanford, James A., Schauer, Irene E., Sealfon, Stuart C., Smith, Kevin S., Smith, Gregory R., Snyder, Michael, Stowe, Cynthia L., Talton, Jennifer W., Teng, Christopher, Thalacker-Mercer, Anna, Tracy, Russell, Trappe, Scott, Trappe, Todd A., Vasoya, Mital, Vetr, Nikolai G., Volpi, Elena, Walkup, Michael P., Wiel, Laurens, Wu, Si, Yan, Zhen, Yu, Jiye, Zaslavsky, Elena, Zebarjadi, Navid, Zhen, Jimmy, Amar, David, Gay, Nicole R., Jimenez-Morales, David, Jean Beltran, Pierre M., Ramaker, Megan E., Raja, Archana Natarajan, Zhao, Bingqing, Sun, Yifei, Marwaha, Shruti, Gaul, David A., Hershman, Steven G., Ferrasse, Alexis, Xia, Ashley, Lanza, Ian, Fernández, Facundo M., Montgomery, Stephen B., Hevener, Andrea L., Ashley, Euan A., Walsh, Martin J., Sparks, Lauren M., Burant, Charles F., Rector, R. Scott, Thyfault, John, Wheeler, Matthew T., Goodpaster, Bret H., Coen, Paul M., Schenk, Simon, Bodine, Sue C., and Lindholm, Malene E.

Published
2024
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4. Multi-ancestry genome-wide gene–sleep interactions identify novel loci for blood pressure

Author

Wang, Heming, Noordam, Raymond, Cade, Brian E, Schwander, Karen, Winkler, Thomas W, Lee, Jiwon, Sung, Yun Ju, Bentley, Amy R, Manning, Alisa K, Aschard, Hugues, Kilpeläinen, Tuomas O, Ilkov, Marjan, Brown, Michael R, Horimoto, Andrea R, Richard, Melissa, Bartz, Traci M, Vojinovic, Dina, Lim, Elise, Nierenberg, Jovia L, Liu, Yongmei, Chitrala, Kumaraswamynaidu, Rankinen, Tuomo, Musani, Solomon K, Franceschini, Nora, Rauramaa, Rainer, Alver, Maris, Zee, Phyllis C, Harris, Sarah E, van der Most, Peter J, Nolte, Ilja M, Munroe, Patricia B, Palmer, Nicholette D, Kühnel, Brigitte, Weiss, Stefan, Wen, Wanqing, Hall, Kelly A, Lyytikäinen, Leo-Pekka, O’Connell, Jeff, Eiriksdottir, Gudny, Launer, Lenore J, de Vries, Paul S, Arking, Dan E, Chen, Han, Boerwinkle, Eric, Krieger, Jose E, Schreiner, Pamela J, Sidney, Stephen, Shikany, James M, Rice, Kenneth, Chen, Yii-Der Ida, Gharib, Sina A, Bis, Joshua C, Luik, Annemarie I, Ikram, M Arfan, Uitterlinden, André G, Amin, Najaf, Xu, Hanfei, Levy, Daniel, He, Jiang, Lohman, Kurt K, Zonderman, Alan B, Rice, Treva K, Sims, Mario, Wilson, Gregory, Sofer, Tamar, Rich, Stephen S, Palmas, Walter, Yao, Jie, Guo, Xiuqing, Rotter, Jerome I, Biermasz, Nienke R, Mook-Kanamori, Dennis O, Martin, Lisa W, Barac, Ana, Wallace, Robert B, Gottlieb, Daniel J, Komulainen, Pirjo, Heikkinen, Sami, Mägi, Reedik, Milani, Lili, Metspalu, Andres, Starr, John M, Milaneschi, Yuri, Waken, RJ, Gao, Chuan, Waldenberger, Melanie, Peters, Annette, Strauch, Konstantin, Meitinger, Thomas, Roenneberg, Till, Völker, Uwe, Dörr, Marcus, Shu, Xiao-Ou, Mukherjee, Sutapa, Hillman, David R, Kähönen, Mika, Wagenknecht, Lynne E, Gieger, Christian, Grabe, Hans J, and Zheng, Wei

Subjects
Human Genome, Sleep Research, Clinical Research, Biotechnology, Hypertension, Genetics, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Blood Pressure, Genetic Loci, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Sleep, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 Pjoint

Published
2021

5. Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.

Author

de Las Fuentes, Lisa, Sung, Yun Ju, Noordam, Raymond, Winkler, Thomas, Feitosa, Mary F, Schwander, Karen, Bentley, Amy R, Brown, Michael R, Guo, Xiuqing, Manning, Alisa, Chasman, Daniel I, Aschard, Hugues, Bartz, Traci M, Bielak, Lawrence F, Campbell, Archie, Cheng, Ching-Yu, Dorajoo, Rajkumar, Hartwig, Fernando P, Horimoto, ARVR, Li, Changwei, Li-Gao, Ruifang, Liu, Yongmei, Marten, Jonathan, Musani, Solomon K, Ntalla, Ioanna, Rankinen, Tuomo, Richard, Melissa, Sim, Xueling, Smith, Albert V, Tajuddin, Salman M, Tayo, Bamidele O, Vojinovic, Dina, Warren, Helen R, Xuan, Deng, Alver, Maris, Boissel, Mathilde, Chai, Jin-Fang, Chen, Xu, Christensen, Kaare, Divers, Jasmin, Evangelou, Evangelos, Gao, Chuan, Girotto, Giorgia, Harris, Sarah E, He, Meian, Hsu, Fang-Chi, Kühnel, Brigitte, Laguzzi, Federica, Li, Xiaoyin, Lyytikäinen, Leo-Pekka, Nolte, Ilja M, Poveda, Alaitz, Rauramaa, Rainer, Riaz, Muhammad, Rueedi, Rico, Shu, Xiao-Ou, Snieder, Harold, Sofer, Tamar, Takeuchi, Fumihiko, Verweij, Niek, Ware, Erin B, Weiss, Stefan, Yanek, Lisa R, Amin, Najaf, Arking, Dan E, Arnett, Donna K, Bergmann, Sven, Boerwinkle, Eric, Brody, Jennifer A, Broeckel, Ulrich, Brumat, Marco, Burke, Gregory, Cabrera, Claudia P, Canouil, Mickaël, Chee, Miao Li, Chen, Yii-Der Ida, Cocca, Massimiliano, Connell, John, de Silva, H Janaka, de Vries, Paul S, Eiriksdottir, Gudny, Faul, Jessica D, Fisher, Virginia, Forrester, Terrence, Fox, Ervin F, Friedlander, Yechiel, Gao, He, Gigante, Bruna, Giulianini, Franco, Gu, Chi Charles, Gu, Dongfeng, Harris, Tamara B, He, Jiang, Heikkinen, Sami, Heng, Chew-Kiat, Hunt, Steven, Ikram, M Arfan, Irvin, Marguerite R, Kähönen, Mika, and Kavousi, Maryam

Subjects
Lifelines Cohort Study, Psychiatry, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P

Published
2021

6. Molecular Transducers of Physical Activity Consortium (MoTrPAC): Mapping the Dynamic Responses to Exercise

Author

Sanford, James A, Nogiec, Christopher D, Lindholm, Malene E, Adkins, Joshua N, Amar, David, Dasari, Surendra, Drugan, Jonelle K, Fernández, Facundo M, Radom-Aizik, Shlomit, Schenk, Simon, Snyder, Michael P, Tracy, Russell P, Vanderboom, Patrick, Trappe, Scott, Walsh, Martin J, Consortium, the Molecular Transducers of Physical Activity, Evans, Charles R, Fernandez, Facundo M, Li, Yafeng, Tomlinson, Lyl, Alekel, D Lee, Bekirov, Iddil, Boyce, Amanda T, Boyington, Josephine, Fleg, Jerome L, Joseph, Lyndon JO, Laughlin, Maren R, Maruvada, Padma, Morris, Stephanie A, McGowan, Joan A, Nierras, Concepcion, Pai, Vinay, Peterson, Charlotte, Ramos, Ed, Roary, Mary C, Williams, John P, Xia, Ashley, Cornell, Elaine, Rooney, Jessica, Miller, Michael E, Ambrosius, Walter T, Rushing, Scott, Stowe, Cynthia L, Rejeski, W Jack, Nicklas, Barbara J, Pahor, Marco, Lu, Ching-ju, Trappe, Todd, Chambers, Toby, Raue, Ulrika, Lester, Bridget, Bergman, Bryan C, Bessesen, David H, Jankowski, Catherine M, Kohrt, Wendy M, Melanson, Edward L, Moreau, Kerrie L, Schauer, Irene E, Schwartz, Robert S, Kraus, William E, Slentz, Cris A, Huffman, Kim M, Johnson, Johanna L, Willis, Leslie H, Kelly, Leslie, Houmard, Joseph A, Dubis, Gabriel, Broskey, Nick, Goodpaster, Bret H, Sparks, Lauren M, Coen, Paul M, Cooper, Dan M, Haddad, Fadia, Rankinen, Tuomo, Ravussin, Eric, Johannsen, Neil, Harris, Melissa, Jakicic, John M, Newman, Anne B, Forman, Daniel D, Kershaw, Erin, Rogers, Renee J, Nindl, Bradley C, Page, Lindsay C, Stefanovic-Racic, Maja, and Barr, Susan L

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Cardiovascular, Evaluation of treatments and therapeutic interventions, 6.7 Physical, Good Health and Well Being, Adolescent, Adult, Animals, Child, Exercise, Female, Humans, Male, Middle Aged, Oxygen Consumption, Physical Endurance, Research Design, Young Adult, Molecular Transducers of Physical Activity Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology, Biological sciences, Biomedical and clinical sciences
Abstract

Exercise provides a robust physiological stimulus that evokes cross-talk among multiple tissues that when repeated regularly (i.e., training) improves physiological capacity, benefits numerous organ systems, and decreases the risk for premature mortality. However, a gap remains in identifying the detailed molecular signals induced by exercise that benefits health and prevents disease. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) was established to address this gap and generate a molecular map of exercise. Preclinical and clinical studies will examine the systemic effects of endurance and resistance exercise across a range of ages and fitness levels by molecular probing of multiple tissues before and after acute and chronic exercise. From this multi-omic and bioinformatic analysis, a molecular map of exercise will be established. Altogether, MoTrPAC will provide a public database that is expected to enhance our understanding of the health benefits of exercise and to provide insight into how physical activity mitigates disease.

Published
2020

7. Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Author

Wu, Peitao, Rybin, Denis, Bielak, Lawrence F, Feitosa, Mary F, Franceschini, Nora, Li, Yize, Lu, Yingchang, Marten, Jonathan, Musani, Solomon K, Noordam, Raymond, Raghavan, Sridharan, Rose, Lynda M, Schwander, Karen, Smith, Albert V, Tajuddin, Salman M, Vojinovic, Dina, Amin, Najaf, Arnett, Donna K, Bottinger, Erwin P, Demirkan, Ayse, Florez, Jose C, Ghanbari, Mohsen, Harris, Tamara B, Launer, Lenore J, Liu, Jingmin, Liu, Jun, Mook-Kanamori, Dennis O, Murray, Alison D, Nalls, Mike A, Peyser, Patricia A, Uitterlinden, André G, Voortman, Trudy, Bouchard, Claude, Chasman, Daniel, Correa, Adolfo, de Mutsert, Renée, Evans, Michele K, Gudnason, Vilmundur, Hayward, Caroline, Kao, Linda, Kardia, Sharon LR, Kooperberg, Charles, Loos, Ruth JF, Province, Michael M, Rankinen, Tuomo, Redline, Susan, Ridker, Paul M, Rotter, Jerome I, Siscovick, David, Smith, Blair H, van Duijn, Cornelia, Zonderman, Alan B, Rao, DC, Wilson, James G, Dupuis, Josée, Meigs, James B, Liu, Ching-Ti, and Vassy, Jason L

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Pharmacology and Pharmaceutical Sciences, Tobacco, Aging, Tobacco Smoke and Health, Human Genome, Nutrition, Diabetes, Clinical Research, Prevention, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Aged, Black People, Blood Glucose, Cigarette Smoking, Cohort Studies, Diabetes Mellitus, Type 2, Fasting, Feasibility Studies, Female, Genetic Loci, Genome-Wide Association Study, Genotype, Humans, Incidence, Male, Middle Aged, Polymorphism, Single Nucleotide, Risk, White People, General Science & Technology
Abstract

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p

Published
2020

8. 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

9. Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Author

Noordam, Raymond, Bos, Maxime M, Wang, Heming, Winkler, Thomas W, Bentley, Amy R, Kilpeläinen, Tuomas O, de Vries, Paul S, Sung, Yun Ju, Schwander, Karen, Cade, Brian E, Manning, Alisa, Aschard, Hugues, Brown, Michael R, Chen, Han, Franceschini, Nora, Musani, Solomon K, Richard, Melissa, Vojinovic, Dina, Aslibekyan, Stella, Bartz, Traci M, de Las Fuentes, Lisa, Feitosa, Mary, Horimoto, Andrea R, Ilkov, Marjan, Kho, Minjung, Kraja, Aldi, Li, Changwei, Lim, Elise, Liu, Yongmei, Mook-Kanamori, Dennis O, Rankinen, Tuomo, Tajuddin, Salman M, van der Spek, Ashley, Wang, Zhe, Marten, Jonathan, Laville, Vincent, Alver, Maris, Evangelou, Evangelos, Graff, Maria E, He, Meian, Kühnel, Brigitte, Lyytikäinen, Leo-Pekka, Marques-Vidal, Pedro, Nolte, Ilja M, Palmer, Nicholette D, Rauramaa, Rainer, Shu, Xiao-Ou, Snieder, Harold, Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R, Adolfo, Correa, Ballantyne, Christie, Bielak, Larry, Biermasz, Nienke R, Boerwinkle, Eric, Dimou, Niki, Eiriksdottir, Gudny, Gao, Chuan, Gharib, Sina A, Gottlieb, Daniel J, Haba-Rubio, José, Harris, Tamara B, Heikkinen, Sami, Heinzer, Raphaël, Hixson, James E, Homuth, Georg, Ikram, M Arfan, Komulainen, Pirjo, Krieger, Jose E, Lee, Jiwon, Liu, Jingmin, Lohman, Kurt K, Luik, Annemarie I, Mägi, Reedik, Martin, Lisa W, Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, Nalls, Mike A, O'Connell, Jeff, Peters, Annette, Peyser, Patricia, Raitakari, Olli T, Reiner, Alex P, Rensen, Patrick CN, Rice, Treva K, Rich, Stephen S, Roenneberg, Till, Rotter, Jerome I, Schreiner, Pamela J, Shikany, James, Sidney, Stephen S, Sims, Mario, Sitlani, Colleen M, Sofer, Tamar, Strauch, Konstantin, Swertz, Morris A, Taylor, Kent D, and Uitterlinden, André G

Subjects
Humans, Lipids, Chromosome Mapping, Sleep, Phylogeny, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Young Adult, Genetic Loci, Polymorphism, Single Nucleotide, and over
Abstract

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

Published
2019

10. Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions

Author

de Vries, Paul S, Brown, Michael R, Bentley, Amy R, Sung, Yun J, Winkler, Thomas W, Ntalla, Ioanna, Schwander, Karen, Kraja, Aldi T, Guo, Xiuqing, Franceschini, Nora, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Huffman, Jennifer E, Musani, Solomon K, Li, Changwei, Feitosa, Mary F, Richard, Melissa A, Noordam, Raymond, Aschard, Hugues, Bartz, Traci M, Bielak, Lawrence F, Deng, Xuan, Dorajoo, Rajkumar, Lohman, Kurt K, Manning, Alisa K, Rankinen, Tuomo, Smith, Albert V, Tajuddin, Salman M, Evangelou, Evangelos, Graff, Mariaelisa, Alver, Maris, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gandin, Ilaria, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E, Hartwig, Fernando P, He, Meian, Horimoto, Andrea RVR, Hsu, Fang-Chi, Jackson, Anne U, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Laguzzi, Federica, Lee, Joseph H, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Matoba, Nana, Nolte, Ilja M, Pietzner, Maik, Riaz, Muhammad, Said, M Abdullah, Scott, Robert A, Sofer, Tamar, Stančáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O, van der Most, Peter J, Varga, Tibor V, Wang, Yajuan, Ware, Erin B, Wen, Wanqing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E, Aung, Tin, Ballantyne, Christie, Boerwinkle, Eric, Broeckel, Ulrich, Campbell, Archie, Canouil, Mickaël, Charumathi, Sabanayagam, Chen, Yii-Der Ida, Connell, John M, de Faire, Ulf, de las Fuentes, Lisa, de Mutsert, Renée, de Silva, H Janaka, Ding, Jingzhong, Dominiczak, Anna F, Duan, Qing, Eaton, Charles B, Eppinga, Ruben N, Faul, Jessica D, Fisher, Virginia, Forrester, Terrence, Franco, Oscar H, Friedlander, Yechiel, Ghanbari, Mohsen, and Giulianini, Franco

Subjects
Epidemiology, Health Sciences, Substance Misuse, Alcoholism, Alcohol Use and Health, Human Genome, Prevention, Genetics, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Adolescent, Adult, Aged, Alcohol Drinking, Cholesterol, HDL, Cholesterol, LDL, Female, Genome-Wide Association Study, Genotype, Humans, Life Style, Lipids, Male, Middle Aged, Phenotype, Racial Groups, Triglycerides, Vascular Endothelial Growth Factor B, Young Adult, alcohol consumption, cholesterol, gene-environment interactions, gene-lifestyle interactions, genome-wide association studies, lipids, triglycerides, InterAct Consortium, Lifelines Cohort, Groningen, The Netherlands, Mathematical Sciences, Medical and Health Sciences
Abstract

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.

Published
2019

11. Adropin: An endocrine link between the biological clock and cholesterol homeostasis

Author

Ghoshal, Sarbani, Stevens, Joseph R, Billon, Cyrielle, Girardet, Clemence, Sitaula, Sadichha, Leon, Arthur S, Rao, DC, Skinner, James S, Rankinen, Tuomo, Bouchard, Claude, Nuñez, Marinelle V, Stanhope, Kimber L, Howatt, Deborah A, Daugherty, Alan, Zhang, Jinsong, Schuelke, Matthew, Weiss, Edward P, Coffey, Alisha R, Bennett, Brian J, Sethupathy, Praveen, Burris, Thomas P, Havel, Peter J, and Butler, Andrew A

Subjects
Biochemistry and Cell Biology, Biological Sciences, Genetics, Atherosclerosis, Nutrition, Digestive Diseases, Liver Disease, Obesity, Prevention, Underpinning research, 1.1 Normal biological development and functioning, Metabolic and endocrine, Adult, Aged, Animals, Blood Proteins, Cells, Cultured, Cholesterol, LDL, Circadian Clocks, Female, Glucose, Hep G2 Cells, Homeostasis, Humans, Intercellular Signaling Peptides and Proteins, Liver, Macaca mulatta, Male, Mice, Middle Aged, Nuclear Receptor Subfamily 1, Group F, Member 1, Nuclear Receptor Subfamily 1, Group F, Member 3, Peptides, Proteins, Cholesterol, LDL, Cardiovascular disease, Adropin, Sex, Physiology, Biochemistry and cell biology
Abstract

ObjectiveIdentify determinants of plasma adropin concentrations, a secreted peptide translated from the Energy Homeostasis Associated (ENHO) gene linked to metabolic control and vascular function.MethodsAssociations between plasma adropin concentrations, demographics (sex, age, BMI) and circulating biomarkers of lipid and glucose metabolism were assessed in plasma obtained after an overnight fast in humans. The regulation of adropin expression was then assessed in silico, in cultured human cells, and in animal models.ResultsIn humans, plasma adropin concentrations are inversely related to atherogenic LDL-cholesterol (LDL-C) levels in men (n = 349), but not in women (n = 401). Analysis of hepatic Enho expression in male mice suggests control by the biological clock. Expression is rhythmic, peaking during maximal food consumption in the dark correlating with transcriptional activation by RORα/γ. The nadir in the light phase coincides with the rest phase and repression by Rev-erb. Plasma adropin concentrations in nonhuman primates (rhesus monkeys) also exhibit peaks coinciding with feeding times (07:00 h, 15:00 h). The ROR inverse agonists SR1001 and the 7-oxygenated sterols 7-β-hydroxysterol and 7-ketocholesterol, or the Rev-erb agonist SR9009, suppress ENHO expression in cultured human HepG2 cells. Consumption of high-cholesterol diets suppress expression of the adropin transcript in mouse liver. However, adropin over expression does not prevent hypercholesterolemia resulting from a high cholesterol diet and/or LDL receptor mutations.ConclusionsIn humans, associations between plasma adropin concentrations and LDL-C suggest a link with hepatic lipid metabolism. Mouse studies suggest that the relationship between adropin and cholesterol metabolism is unidirectional, and predominantly involves suppression of adropin expression by cholesterol and 7-oxygenated sterols. Sensing of fatty acids, cholesterol and oxysterols by the RORα/γ ligand-binding domain suggests a plausible functional link between adropin expression and cellular lipid metabolism. Furthermore, the nuclear receptors RORα/γ and Rev-erb may couple adropin synthesis with circadian rhythms in carbohydrate and lipid metabolism.

Published
2018

12. Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.

Author

Feitosa, Mary F, Kraja, Aldi T, Chasman, Daniel I, Sung, Yun J, Winkler, Thomas W, Ntalla, Ioanna, Guo, Xiuqing, Franceschini, Nora, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Marten, Jonathan, Musani, Solomon K, Li, Changwei, Bentley, Amy R, Brown, Michael R, Schwander, Karen, Richard, Melissa A, Noordam, Raymond, Aschard, Hugues, Bartz, Traci M, Bielak, Lawrence F, Dorajoo, Rajkumar, Fisher, Virginia, Hartwig, Fernando P, Horimoto, Andrea RVR, Lohman, Kurt K, Manning, Alisa K, Rankinen, Tuomo, Smith, Albert V, Tajuddin, Salman M, Wojczynski, Mary K, Alver, Maris, Boissel, Mathilde, Cai, Qiuyin, Campbell, Archie, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E, He, Meian, Hsu, Fang-Chi, Jackson, Anne U, Kähönen, Mika, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Laguzzi, Federica, Luan, Jian'an, Matoba, Nana, Nolte, Ilja M, Padmanabhan, Sandosh, Riaz, Muhammad, Rueedi, Rico, Robino, Antonietta, Said, M Abdullah, Scott, Robert A, Sofer, Tamar, Stančáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O, van der Most, Peter J, Varga, Tibor V, Vitart, Veronique, Wang, Yajuan, Ware, Erin B, Warren, Helen R, Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E, Aung, Tin, Boerwinkle, Eric, Borecki, Ingrid, Broeckel, Ulrich, Brown, Morris, Brumat, Marco, Burke, Gregory L, Canouil, Mickaël, Chakravarti, Aravinda, Charumathi, Sabanayagam, Ida Chen, Yii-Der, Connell, John M, Correa, Adolfo, de Las Fuentes, Lisa, de Mutsert, Renée, de Silva, H Janaka, Deng, Xuan, Ding, Jingzhong, Duan, Qing, Eaton, Charles B, and Ehret, Georg

Subjects
InterAct Consortium, Humans, Hypertension, Genetic Predisposition to Disease, Cohort Studies, Pedigree, Alcohol Drinking, Blood Pressure, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Continental Population Groups, Female, Male, Genome-Wide Association Study, Young Adult, Gene-Environment Interaction, General Science & Technology
Abstract

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

Published
2018

13. An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene‐Lifestyle Interactions Working Group

Author

Sung, Yun Ju, Winkler, Thomas W, Manning, Alisa K, Aschard, Hugues, Gudnason, Vilmundur, Harris, Tamara B, Smith, Albert V, Boerwinkle, Eric, Brown, Michael R, Morrison, Alanna C, Fornage, Myriam, Lin, Li-An, Richard, Melissa, Bartz, Traci M, Psaty, Bruce M, Hayward, Caroline, Polasek, Ozren, Marten, Jonathan, Rudan, Igor, Feitosa, Mary F, Kraja, Aldi T, Province, Michael A, Deng, Xuan, Fisher, Virginia A, Zhou, Yanhua, Bielak, Lawrence F, Smith, Jennifer, Huffman, Jennifer E, Padmanabhan, Sandosh, Smith, Blair H, Ding, Jingzhong, Liu, Yongmei, Lohman, Kurt, Bouchard, Claude, Rankinen, Tuomo, Rice, Treva K, Arnett, Donna, Schwander, Karen, Guo, Xiuqing, Palmas, Walter, Rotter, Jerome I, Alfred, Tamuno, Bottinger, Erwin P, Loos, Ruth JF, Amin, Najaf, Franco, Oscar H, van Duijn, Cornelia M, Vojinovic, Dina, Chasman, Daniel I, Ridker, Paul M, Rose, Lynda M, Kardia, Sharon, Zhu, Xiaofeng, Rice, Kenneth, Borecki, Ingrid B, Rao, Dabeeru C, Gauderman, W James, and Cupples, L Adrienne

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Clinical Research, Human Genome, Blood Pressure, Cohort Studies, Databases, Factual, Family, Gene Frequency, Gene-Environment Interaction, Genome-Wide Association Study, Genotype, Humans, Phenotype, Smoking, gene-environment interaction, meta-analysis, low-frequency variants, Public Health and Health Services
Abstract

Studying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions uses a single regression model that includes both the genetic main and G × E interaction effects (the "joint" framework). The alternative "stratified" framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.

Published
2016

14. Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Author

Kilpeläinen, Tuomas O, Carli, Jayne F Martin, Skowronski, Alicja A, Sun, Qi, Kriebel, Jennifer, Feitosa, Mary F, Hedman, Åsa K, Drong, Alexander W, Hayes, James E, Zhao, Jinghua, Pers, Tune H, Schick, Ursula, Grarup, Niels, Kutalik, Zoltán, Trompet, Stella, Mangino, Massimo, Kristiansson, Kati, Beekman, Marian, Lyytikäinen, Leo-Pekka, Eriksson, Joel, Henneman, Peter, Lahti, Jari, Tanaka, Toshiko, Luan, Jian'an, Del Greco M, Fabiola, Pasko, Dorota, Renström, Frida, Willems, Sara M, Mahajan, Anubha, Rose, Lynda M, Guo, Xiuqing, Liu, Yongmei, Kleber, Marcus E, Pérusse, Louis, Gaunt, Tom, Ahluwalia, Tarunveer S, Ju Sung, Yun, Ramos, Yolande F, Amin, Najaf, Amuzu, Antoinette, Barroso, Inês, Bellis, Claire, Blangero, John, Buckley, Brendan M, Böhringer, Stefan, I Chen, Yii-Der, de Craen, Anton JN, Crosslin, David R, Dale, Caroline E, Dastani, Zari, Day, Felix R, Deelen, Joris, Delgado, Graciela E, Demirkan, Ayse, Finucane, Francis M, Ford, Ian, Garcia, Melissa E, Gieger, Christian, Gustafsson, Stefan, Hallmans, Göran, Hankinson, Susan E, Havulinna, Aki S, Herder, Christian, Hernandez, Dena, Hicks, Andrew A, Hunter, David J, Illig, Thomas, Ingelsson, Erik, Ioan-Facsinay, Andreea, Jansson, John-Olov, Jenny, Nancy S, Jørgensen, Marit E, Jørgensen, Torben, Karlsson, Magnus, Koenig, Wolfgang, Kraft, Peter, Kwekkeboom, Joanneke, Laatikainen, Tiina, Ladwig, Karl-Heinz, LeDuc, Charles A, Lowe, Gordon, Lu, Yingchang, Marques-Vidal, Pedro, Meisinger, Christa, Menni, Cristina, Morris, Andrew P, Myers, Richard H, Männistö, Satu, Nalls, Mike A, Paternoster, Lavinia, Peters, Annette, Pradhan, Aruna D, Rankinen, Tuomo, Rasmussen-Torvik, Laura J, Rathmann, Wolfgang, Rice, Treva K, Brent Richards, J, Ridker, Paul M, Sattar, Naveed, and Savage, David B

Subjects
Adipose Tissue, Animals, Mice, Leptin, RNA, Messenger, Tissue Culture Techniques, Gene Expression Regulation, Male, Genome-Wide Association Study, Gene Knockdown Techniques, RNA, Messenger
Abstract

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P

Published
2016

15. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci

Author

de las Fuentes, Lisa, primary, Schwander, Karen L., additional, Brown, Michael R., additional, Bentley, Amy R., additional, Winkler, Thomas W., additional, Sung, Yun Ju, additional, Munroe, Patricia B., additional, Miller, Clint L., additional, Aschard, Hugo, additional, Aslibekyan, Stella, additional, Bartz, Traci M., additional, Bielak, Lawrence F., additional, Chai, Jin Fang, additional, Cheng, Ching-Yu, additional, Dorajoo, Rajkumar, additional, Feitosa, Mary F., additional, Guo, Xiuqing, additional, Hartwig, Fernando P., additional, Horimoto, Andrea, additional, Kolčić, Ivana, additional, Lim, Elise, additional, Liu, Yongmei, additional, Manning, Alisa K., additional, Marten, Jonathan, additional, Musani, Solomon K., additional, Noordam, Raymond, additional, Padmanabhan, Sandosh, additional, Rankinen, Tuomo, additional, Richard, Melissa A., additional, Ridker, Paul M., additional, Smith, Albert V., additional, Vojinovic, Dina, additional, Zonderman, Alan B., additional, Alver, Maris, additional, Boissel, Mathilde, additional, Christensen, Kaare, additional, Freedman, Barry I., additional, Gao, Chuan, additional, Giulianini, Franco, additional, Harris, Sarah E., additional, He, Meian, additional, Hsu, Fang-Chi, additional, Kühnel, Brigitte, additional, Laguzzi, Federica, additional, Li, Xiaoyin, additional, Lyytikäinen, Leo-Pekka, additional, Nolte, Ilja M., additional, Poveda, Alaitz, additional, Rauramaa, Rainer, additional, Riaz, Muhammad, additional, Robino, Antonietta, additional, Sofer, Tamar, additional, Takeuchi, Fumihiko, additional, Tayo, Bamidele O., additional, van der Most, Peter J., additional, Verweij, Niek, additional, Ware, Erin B., additional, Weiss, Stefan, additional, Wen, Wanqing, additional, Yanek, Lisa R., additional, Zhan, Yiqiang, additional, Amin, Najaf, additional, Arking, Dan E., additional, Ballantyne, Christie, additional, Boerwinkle, Eric, additional, Brody, Jennifer A., additional, Broeckel, Ulrich, additional, Campbell, Archie, additional, Canouil, Mickaël, additional, Chai, Xiaoran, additional, Chen, Yii-Der Ida, additional, Chen, Xu, additional, Chitrala, Kumaraswamy Naidu, additional, Concas, Maria Pina, additional, de Faire, Ulf, additional, de Mutsert, Renée, additional, de Silva, H. Janaka, additional, de Vries, Paul S., additional, Do, Ahn, additional, Faul, Jessica D., additional, Fisher, Virginia, additional, Floyd, James S., additional, Forrester, Terrence, additional, Friedlander, Yechiel, additional, Girotto, Giorgia, additional, Gu, C. Charles, additional, Hallmans, Göran, additional, Heikkinen, Sami, additional, Heng, Chew-Kiat, additional, Homuth, Georg, additional, Hunt, Steven, additional, Ikram, M. Arfan, additional, Jacobs, David R., additional, Kavousi, Maryam, additional, Khor, Chiea Chuen, additional, Kilpeläinen, Tuomas O., additional, Koh, Woon-Puay, additional, Komulainen, Pirjo, additional, Langefeld, Carl D., additional, Liang, Jingjing, additional, Liu, Kiang, additional, Liu, Jianjun, additional, Lohman, Kurt, additional, Mägi, Reedik, additional, Manichaikul, Ani W., additional, McKenzie, Colin A., additional, Meitinger, Thomas, additional, Milaneschi, Yuri, additional, Nauck, Matthias, additional, Nelson, Christopher P., additional, O’Connell, Jeffrey R., additional, Palmer, Nicholette D., additional, Pereira, Alexandre C., additional, Perls, Thomas, additional, Peters, Annette, additional, Polašek, Ozren, additional, Raitakari, Olli T., additional, Rice, Kenneth, additional, Rice, Treva K., additional, Rich, Stephen S., additional, Sabanayagam, Charumathi, additional, Schreiner, Pamela J., additional, Shu, Xiao-Ou, additional, Sidney, Stephen, additional, Sims, Mario, additional, Smith, Jennifer A., additional, Starr, John M., additional, Strauch, Konstantin, additional, Tai, E. Shyong, additional, Taylor, Kent D., additional, Tsai, Michael Y., additional, Uitterlinden, André G., additional, van Heemst, Diana, additional, Waldenberger, Melanie, additional, Wang, Ya-Xing, additional, Wei, Wen-Bin, additional, Wilson, Gregory, additional, Xuan, Deng, additional, Yao, Jie, additional, Yu, Caizheng, additional, Yuan, Jian-Min, additional, Zhao, Wei, additional, Becker, Diane M., additional, Bonnefond, Amélie, additional, Bowden, Donald W., additional, Cooper, Richard S., additional, Deary, Ian J., additional, Divers, Jasmin, additional, Esko, Tõnu, additional, Franks, Paul W., additional, Froguel, Philippe, additional, Gieger, Christian, additional, Jonas, Jost B., additional, Kato, Norihiro, additional, Lakka, Timo A., additional, Leander, Karin, additional, Lehtimäki, Terho, additional, Magnusson, Patrik K. E., additional, North, Kari E., additional, Ntalla, Ioanna, additional, Penninx, Brenda, additional, Samani, Nilesh J., additional, Snieder, Harold, additional, Spedicati, Beatrice, additional, van der Harst, Pim, additional, Völzke, Henry, additional, Wagenknecht, Lynne E., additional, Weir, David R., additional, Wojczynski, Mary K., additional, Wu, Tangchun, additional, Zheng, Wei, additional, Zhu, Xiaofeng, additional, Bouchard, Claude, additional, Chasman, Daniel I., additional, Evans, Michele K., additional, Fox, Ervin R., additional, Gudnason, Vilmundur, additional, Hayward, Caroline, additional, Horta, Bernardo L., additional, Kardia, Sharon L. R., additional, Krieger, Jose Eduardo, additional, Mook-Kanamori, Dennis O., additional, Peyser, Patricia A., additional, Province, Michael M., additional, Psaty, Bruce M., additional, Rudan, Igor, additional, Sim, Xueling, additional, Smith, Blair H., additional, van Dam, Rob M., additional, van Duijn, Cornelia M., additional, Wong, Tien Yin, additional, Arnett, Donna K., additional, Rao, Dabeeru C., additional, Gauderman, James, additional, Liu, Ching-Ti, additional, Morrison, Alanna C., additional, Rotter, Jerome I., additional, and Fornage, Myriam, additional

Published
2023
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17. Dose-Response Issues Concerning the Relations between Regular Physical Activity and Health.

Author

President's Council on Physical Fitness and Sports, Washington, DC., Rankinen, Tuomo, and Bouchard, Claude

Abstract

This paper categorizes the many benefits of physical activity, offering information concerning the type of dose necessary to get that benefit. In 2000, Health Canada and the United States Centers for Disease Control and Prevention, along with other agencies, sponsored a symposium to determine whether there was a dose-response relationship between physical activity and several health related outcomes. A group of 24 experts from six countries reviewed the published research on several health outcomes (all-cause mortality, cardiovascular disease, type 2 diabetes mellitus, cancer, blood pressure, body weight and body composition, bone density, blood lipids and lipoproteins, hemostatic factors, low back pain and osteoarthritis, and quality of life and independent living in the elderly, depression, and anxiety. Results showed ample evidence supporting the beneficial effects of regular physical activity on all reviewed health outcomes. There was a strong suggestion of an inverse and linear relationship between regular physical activity and rates of all-cause mortality, total cardiovascular disease, coronary heart disease incidence and mortality, and incidence of type 2 diabetes mellitus. For other health outcomes, the dose-response relationship with physical activity was less clear. (Contains 15 references.) (SM)

Published
2002

20. Plasma steroids, body composition, and fat distribution: effects of age, sex, and exercise training

Author

He, Zihong, Rankinen, Tuomo, Leon, Arthur, Skinner, James, Tchernof, André, and Bouchard, Claude

Abstract

Plasma steroid hormone levels vary between men and women, but their associations with BMI and adiposity are controversial. Furthermore, little is known about the role of exercise programs on the relationship between steroid hormones and adiposity. This report evaluates these relationships for plasma levels of adrenal, gonadal, and conjugated steroids with body composition and fat distribution in sedentary men and women, aged 17–65 years, and their responses to an exercise program. In the sedentary state, 270 men (29% Blacks) and 304 women (34% Blacks) from the HERITAGE Family Study were available. Among them, 242 men and 238 women completed a 20-week fully standardized exercise program. Fourteen steroid hormones and SHBG concentrations were assayed in a fasted state and were compared for their associations with adiposity in men and women and in response to the exercise program. Covariates adjusted for in partial correlation analysis were age, ancestry, menopause status (women), and oral contraceptives/hormone replacement treatment status (women) at baseline, as well as baseline value of the trait for the training response. Differences among normal weight, overweight, and obese subjects were also considered. Statistical significance was set at P< 0.0001. Baseline levels of dihydrotesterone (DHT), 17 hydroxy progesterone (OHPROG), sex hormone-binding globulin (SHBG), and testosterone (TESTO) were negatively associated with fat mass and abdominal fat (P< 0.0001) in men and for SHBG in women (P< 0.0001). TESTO was not correlated with fat-free mass in men or women, but was significantly associated with % fat-free mass in men. No association was detected between baseline steroid hormone levels and changes in adiposity traits in response to 20 weeks of exercise. In men, low DHT, OHPROG, SHBG, and TESTO were associated with higher adiposity and abdominal and visceral fat. A similar adiposity profile was observed in women with low SHBG.

Published
2024
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24. β-Aminoisobutyric Acid Induces Browning of White Fat and Hepatic β-Oxidation and Is Inversely Correlated with Cardiometabolic Risk Factors

Author

Roberts, Lee D., Boström, Pontus, O’Sullivan, John F., Schinzel, Robert T., Lewis, Gregory D., Dejam, Andre, Lee, Youn-Kyoung, Palma, Melinda J., Calhoun, Sondra, Georgiadi, Anastasia, Chen, Ming-Huei, Ramachandran, Vasan S., Larson, Martin G., Bouchard, Claude, Rankinen, Tuomo, Souza, Amanda L., Clish, Clary B., Wang, Thomas J., Estall, Jennifer L., Soukas, Alexander A., Cowan, Chad A., Spiegelman, Bruce M., and Gerszten, Robert E.

Published
2014
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31. Genetic studies of body mass index yield new insights for obesity biology

Author

Locke, Adam E., Kahali, Bratati, Berndt, Sonja I., Justice, Anne E., Pers, Tune H., Day, Felix R., Powell, Corey, Vedantam, Sailaja, Buchkovich, Martin L., Yang, Jian, Croteau-Chonka, Damien C., Esko, Tonu, Fall, Tove, Ferreira, Teresa, Gustafsson, Stefan, Kutalik, Zoltán, Luan, Jianʼan, Mägi, Reedik, Randall, Joshua C., Winkler, Thomas W., Wood, Andrew R., Workalemahu, Tsegaselassie, Faul, Jessica D., Smith, Jennifer A., Hua Zhao, Jing, Zhao, Wei, Chen, Jin, Fehrmann, Rudolf, Hedman, Åsa K., Karjalainen, Juha, Schmidt, Ellen M., Absher, Devin, Amin, Najaf, Anderson, Denise, Beekman, Marian, Bolton, Jennifer L., Bragg-Gresham, Jennifer L., Buyske, Steven, Demirkan, Ayse, Deng, Guohong, Ehret, Georg B., Feenstra, Bjarke, Feitosa, Mary F., Fischer, Krista, Goel, Anuj, Gong, Jian, Jackson, Anne U., Kanoni, Stavroula, Kleber, Marcus E., Kristiansson, Kati, Lim, Unhee, Lotay, Vaneet, Mangino, Massimo, Mateo Leach, Irene, Medina-Gomez, Carolina, Medland, Sarah E., Nalls, Michael A., Palmer, Cameron D., Pasko, Dorota, Pechlivanis, Sonali, Peters, Marjolein J., Prokopenko, Inga, Shungin, Dmitry, Stančáková, Alena, Strawbridge, Rona J., Ju Sung, Yun, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, van der Laan, Sander W., van Setten, Jessica, Van Vliet-Ostaptchouk, Jana V., Wang, Zhaoming, Yengo, Loïc, Zhang, Weihua, Isaacs, Aaron, Albrecht, Eva, Ärnlöv, Johan, Arscott, Gillian M., Attwood, Antony P., Bandinelli, Stefania, Barrett, Amy, Bas, Isabelita N., Bellis, Claire, Bennett, Amanda J., Berne, Christian, Blagieva, Roza, Blüher, Matthias, Böhringer, Stefan, Bonnycastle, Lori L., Böttcher, Yvonne, Boyd, Heather A., Bruinenberg, Marcel, Caspersen, Ida H., Ida Chen, Yii-Der, Clarke, Robert, Warwick Daw, E., de Craen, Anton J. M., Delgado, Graciela, Dimitriou, Maria, Doney, Alex S. F., Eklund, Niina, Estrada, Karol, Eury, Elodie, Folkersen, Lasse, Fraser, Ross M., Garcia, Melissa E., Geller, Frank, Giedraitis, Vilmantas, Gigante, Bruna, Go, Alan S., Golay, Alain, Goodall, Alison H., Gordon, Scott D., Gorski, Mathias, Grabe, Hans-Jörgen, Grallert, Harald, Grammer, Tanja B., Gräler, Jürgen, Grönberg, Henrik, Groves, Christopher J., Gusto, Gaëlle, Haessler, Jeffrey, Hall, Per, Haller, Toomas, Hallmans, Goran, Hartman, Catharina A., Hassinen, Maija, Hayward, Caroline, Heard-Costa, Nancy L., Helmer, Quinta, Hengstenberg, Christian, Holmen, Oddgeir, Hottenga, Jouke-Jan, James, Alan L., Jeff, Janina M., Johansson, Åsa, Jolley, Jennifer, Juliusdottir, Thorhildur, Kinnunen, Leena, Koenig, Wolfgang, Koskenvuo, Markku, Kratzer, Wolfgang, Laitinen, Jaana, Lamina, Claudia, Leander, Karin, Lee, Nanette R., Lichtner, Peter, Lind, Lars, Lindström, Jaana, Sin Lo, Ken, Lobbens, Stéphane, Lorbeer, Roberto, Lu, Yingchang, Mach, François, Magnusson, Patrik K. E., Mahajan, Anubha, McArdle, Wendy L., McLachlan, Stela, Menni, Cristina, Merger, Sigrun, Mihailov, Evelin, Milani, Lili, Moayyeri, Alireza, Monda, Keri L., Morken, Mario A., Mulas, Antonella, Müller, Gabriele, Müller-Nurasyid, Martina, Musk, Arthur W., Nagaraja, Ramaiah, Nöthen, Markus M., Nolte, Ilja M., Pilz, Stefan, Rayner, Nigel W., Renstrom, Frida, Rettig, Rainer, Ried, Janina S., Ripke, Stephan, Robertson, Neil R., Rose, Lynda M., Sanna, Serena, Scharnagl, Hubert, Scholtens, Salome, Schumacher, Fredrick R., Scott, William R., Seufferlein, Thomas, Shi, Jianxin, Vernon Smith, Albert, Smolonska, Joanna, Stanton, Alice V., Steinthorsdottir, Valgerdur, Stirrups, Kathleen, Stringham, Heather M., Sundström, Johan, Swertz, Morris A., Swift, Amy J., Syvänen, Ann-Christine, Tan, Sian-Tsung, Tayo, Bamidele O., Thorand, Barbara, Thorleifsson, Gudmar, Tyrer, Jonathan P., Uh, Hae-Won, Vandenput, Liesbeth, Verhulst, Frank C., Vermeulen, Sita H., Verweij, Niek, Vonk, Judith M., Waite, Lindsay L., Warren, Helen R., Waterworth, Dawn, Weedon, Michael N., Wilkens, Lynne R., Willenborg, Christina, Wilsgaard, Tom, Wojczynski, Mary K., Wong, Andrew, Wright, Alan F., Zhang, Qunyuan, Brennan, Eoin P., Choi, Murim, Dastani, Zari, Drong, Alexander W., Eriksson, Per, Franco-Cereceda, Anders, Gådin, Jesper R., Gharavi, Ali G., Goddard, Michael E., Handsaker, Robert E., Huang, Jinyan, Karpe, Fredrik, Kathiresan, Sekar, Keildson, Sarah, Kiryluk, Krzysztof, Kubo, Michiaki, Lee, Jong-Young, Liang, Liming, Lifton, Richard P., Ma, Baoshan, McCarroll, Steven A., McKnight, Amy J., Min, Josine L., Moffatt, Miriam F., Montgomery, Grant W., Murabito, Joanne M., Nicholson, George, Nyholt, Dale R., Okada, Yukinori, Perry, John R. B., Dorajoo, Rajkumar, Reinmaa, Eva, Salem, Rany M., Sandholm, Niina, Scott, Robert A., Stolk, Lisette, Takahashi, Atsushi, Tanaka, Toshihiro, vanʼt Hooft, Ferdinand M., Vinkhuyzen, Anna A. E., Westra, Harm-Jan, Zheng, Wei, Zondervan, Krina T., Heath, Andrew C., Arveiler, Dominique, Bakker, Stephan J. L., Beilby, John, Bergman, Richard N., Blangero, John, Bovet, Pascal, Campbell, Harry, Caulfield, Mark J., Cesana, Giancarlo, Chakravarti, Aravinda, Chasman, Daniel I., Chines, Peter S., Collins, Francis S., Crawford, Dana C., Adrienne Cupples, L., Cusi, Daniele, Danesh, John, de Faire, Ulf, den Ruijter, Hester M., Dominiczak, Anna F., Erbel, Raimund, Erdmann, Jeanette, Eriksson, Johan G., Farrall, Martin, Felix, Stephan B., Ferrannini, Ele, Ferrières, Jean, Ford, Ian, Forouhi, Nita G., Forrester, Terrence, Franco, Oscar H., Gansevoort, Ron T., Gejman, Pablo V., Gieger, Christian, Gottesman, Omri, Gudnason, Vilmundur, Gyllensten, Ulf, Hall, Alistair S., Harris, Tamara B., Hattersley, Andrew T., Hicks, Andrew A., Hindorff, Lucia A., Hingorani, Aroon D., Hofman, Albert, Homuth, Georg, Kees Hovingh, G., Humphries, Steve E., Hunt, Steven C., Hyppönen, Elina, Illig, Thomas, Jacobs, Kevin B., Jarvelin, Marjo-Riitta, Jöckel, Karl-Heinz, Johansen, Berit, Jousilahti, Pekka, Wouter Jukema, J., Jula, Antti M., Kaprio, Jaakko, Kastelein, John J. P., Keinanen-Kiukaanniemi, Sirkka M., Kiemeney, Lambertus A., Knekt, Paul, Kooner, Jaspal S., Kooperberg, Charles, Kovacs, Peter, Kraja, Aldi T., Kumari, Meena, Kuusisto, Johanna, Lakka, Timo A., Langenberg, Claudia, Le Marchand, Loic, Lehtimäki, Terho, Lyssenko, Valeriya, Männistö, Satu, Marette, André, Matise, Tara C., McKenzie, Colin A., McKnight, Barbara, Moll, Frans L., Morris, Andrew D., Morris, Andrew P., Murray, Jeffrey C., Nelis, Mari, Ohlsson, Claes, Oldehinkel, Albertine J., Ong, Ken K., Madden, Pamela A. F., Pasterkamp, Gerard, Peden, John F., Peters, Annette, Postma, Dirkje S., Pramstaller, Peter P., Price, Jackie F., Qi, Lu, Raitakari, Olli T., Rankinen, Tuomo, Rao, D. C., Rice, Treva K., Ridker, Paul M., Rioux, John D., Ritchie, Marylyn D., Rudan, Igor, Salomaa, Veikko, Samani, Nilesh J., Saramies, Jouko, Sarzynski, Mark A., Schunkert, Heribert, Schwarz, Peter E. H., Sever, Peter, Shuldiner, Alan R., Sinisalo, Juha, Stolk, Ronald P., Strauch, Konstantin, Tönjes, Anke, Trégouët, David-Alexandre, Tremblay, Angelo, Tremoli, Elena, Virtamo, Jarmo, Vohl, Marie-Claude, Völker, Uwe, Waeber, Gérard, Willemsen, Gonneke, Witteman, Jacqueline C., Carola Zillikens, M., Adair, Linda S., Amouyel, Philippe, Asselbergs, Folkert W., Assimes, Themistocles L., Bochud, Murielle, Boehm, Bernhard O., Boerwinkle, Eric, Bornstein, Stefan R., Bottinger, Erwin P., Bouchard, Claude, Cauchi, Stéphane, Chambers, John C., Chanock, Stephen J., Cooper, Richard S., de Bakker, Paul I. W., Dedoussis, George, Ferrucci, Luigi, Franks, Paul W., Froguel, Philippe, Groop, Leif C., Haiman, Christopher A., Hamsten, Anders, Hui, Jennie, Hunter, David J., Hveem, Kristian, Kaplan, Robert C., Kivimaki, Mika, Kuh, Diana, Laakso, Markku, Liu, Yongmei, Martin, Nicholas G., März, Winfried, Melbye, Mads, Metspalu, Andres, Moebus, Susanne, Munroe, Patricia B., Njølstad, Inger, Oostra, Ben A., Palmer, Colin N. A., Pedersen, Nancy L., Perola, Markus, Pérusse, Louis, Peters, Ulrike, Power, Chris, Quertermous, Thomas, Rauramaa, Rainer, Rivadeneira, Fernando, Saaristo, Timo E., Saleheen, Danish, Sattar, Naveed, Schadt, Eric E., Schlessinger, David, Eline Slagboom, P., Snieder, Harold, Spector, Tim D., Thorsteinsdottir, Unnur, Stumvoll, Michael, Tuomilehto, Jaakko, Uitterlinden, André G., Uusitupa, Matti, van der Harst, Pim, Walker, Mark, Wallaschofski, Henri, Wareham, Nicholas J., Watkins, Hugh, Weir, David R., Wichmann, H-Erich, Wilson, James F., Zanen, Pieter, Borecki, Ingrid B., Deloukas, Panos, Fox, Caroline S., Heid, Iris M., OʼConnell, Jeffrey R., Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Abecasis, Gonçalo R., Franke, Lude, Frayling, Timothy M., McCarthy, Mark I., Visscher, Peter M., Scherag, André, Willer, Cristen J., Boehnke, Michael, Mohlke, Karen L., Lindgren, Cecilia M., Beckmann, Jacques S., Barroso, Inês, North, Kari E., Ingelsson, Erik, Hirschhorn, Joel N., Loos, Ruth J. F., and Speliotes, Elizabeth K.

Published
2015
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32. New genetic loci link adipose and insulin biology to body fat distribution

Author

Shungin, Dmitry, Winkler, Thomas W., Croteau-Chonka, Damien C., Ferreira, Teresa, Locke, Adam E., Mägi, Reedik, Strawbridge, Rona J., Pers, Tune H., Fischer, Krista, Justice, Anne E., Workalemahu, Tsegaselassie, Wu, Joseph M. W., Buchkovich, Martin L., Heard-Costa, Nancy L., Roman, Tamara S., Drong, Alexander W., Song, Ci, Gustafsson, Stefan, Day, Felix R., Esko, Tonu, Fall, Tove, Kutalik, Zoltán, Luan, Jianʼan, Randall, Joshua C., Scherag, André, Vedantam, Sailaja, Wood, Andrew R., Chen, Jin, Fehrmann, Rudolf, Karjalainen, Juha, Kahali, Bratati, Liu, Ching-Ti, Schmidt, Ellen M., Absher, Devin, Amin, Najaf, Anderson, Denise, Beekman, Marian, Bragg-Gresham, Jennifer L., Buyske, Steven, Demirkan, Ayse, Ehret, Georg B., Feitosa, Mary F., Goel, Anuj, Jackson, Anne U., Johnson, Toby, Kleber, Marcus E., Kristiansson, Kati, Mangino, Massimo, Mateo Leach, Irene, Medina-Gomez, Carolina, Palmer, Cameron D., Pasko, Dorota, Pechlivanis, Sonali, Peters, Marjolein J., Prokopenko, Inga, Stančáková, Alena, Ju Sung, Yun, Tanaka, Toshiko, Teumer, Alexander, Van Vliet-Ostaptchouk, Jana V., Yengo, Loïc, Zhang, Weihua, Albrecht, Eva, Ärnlöv, Johan, Arscott, Gillian M., Bandinelli, Stefania, Barrett, Amy, Bellis, Claire, Bennett, Amanda J., Berne, Christian, Blüher, Matthias, Böhringer, Stefan, Bonnet, Fabrice, Böttcher, Yvonne, Bruinenberg, Marcel, Carba, Delia B., Caspersen, Ida H., Clarke, Robert, Warwick Daw, E., Deelen, Joris, Deelman, Ewa, Delgado, Graciela, Doney, Alex S. F., Eklund, Niina, Erdos, Michael R., Estrada, Karol, Eury, Elodie, Friedrich, Nele, Garcia, Melissa E., Giedraitis, Vilmantas, Gigante, Bruna, Go, Alan S., Golay, Alain, Grallert, Harald, Grammer, Tanja B., Gräler, Jürgen, Grewal, Jagvir, Groves, Christopher J., Haller, Toomas, Hallmans, Goran, Hartman, Catharina A., Hassinen, Maija, Hayward, Caroline, Heikkilä, Kauko, Herzig, Karl-Heinz, Helmer, Quinta, Hillege, Hans L., Holmen, Oddgeir, Hunt, Steven C., Isaacs, Aaron, Ittermann, Till, James, Alan L., Johansson, Ingegerd, Juliusdottir, Thorhildur, Kalafati, Ioanna-Panagiota, Kinnunen, Leena, Koenig, Wolfgang, Kooner, Ishminder K., Kratzer, Wolfgang, Lamina, Claudia, Leander, Karin, Lee, Nanette R., Lichtner, Peter, Lind, Lars, Lindström, Jaana, Lobbens, Stéphane, Lorentzon, Mattias, Mach, François, Magnusson, Patrik K. E., Mahajan, Anubha, McArdle, Wendy L., Menni, Cristina, Merger, Sigrun, Mihailov, Evelin, Milani, Lili, Mills, Rebecca, Moayyeri, Alireza, Monda, Keri L., Mooijaart, Simon P., Mühleisen, Thomas W., Mulas, Antonella, Müller, Gabriele, Müller-Nurasyid, Martina, Nagaraja, Ramaiah, Nalls, Michael A., Narisu, Narisu, Glorioso, Nicola, Nolte, Ilja M., Olden, Matthias, Rayner, Nigel W., Renstrom, Frida, Ried, Janina S., Robertson, Neil R., Rose, Lynda M., Sanna, Serena, Scharnagl, Hubert, Scholtens, Salome, Sennblad, Bengt, Seufferlein, Thomas, Sitlani, Colleen M., Vernon Smith, Albert, Stirrups, Kathleen, Stringham, Heather M., Sundström, Johan, Swertz, Morris A., Swift, Amy J., Syvänen, Ann-Christine, Tayo, Bamidele O., Thorand, Barbara, Thorleifsson, Gudmar, Tomaschitz, Andreas, Troffa, Chiara, van Oort, Floor V. A., Verweij, Niek, Vonk, Judith M., Waite, Lindsay L., Wennauer, Roman, Wilsgaard, Tom, Wojczynski, Mary K., Wong, Andrew, Zhang, Qunyuan, Hua Zhao, Jing, Brennan, Eoin P., Choi, Murim, Eriksson, Per, Folkersen, Lasse, Franco-Cereceda, Anders, Gharavi, Ali G., Hedman, Åsa K., Hivert, Marie-France, Huang, Jinyan, Kanoni, Stavroula, Karpe, Fredrik, Keildson, Sarah, Kiryluk, Krzysztof, Liang, Liming, Lifton, Richard P., Ma, Baoshan, McKnight, Amy J., McPherson, Ruth, Metspalu, Andres, Min, Josine L., Moffatt, Miriam F., Montgomery, Grant W., Murabito, Joanne M., Nicholson, George, Nyholt, Dale R., Olsson, Christian, Perry, John R. B., Reinmaa, Eva, Salem, Rany M., Sandholm, Niina, Schadt, Eric E., Scott, Robert A., Stolk, Lisette, Vallejo, Edgar E., Westra, Harm-Jan, Zondervan, Krina T., Amouyel, Philippe, Arveiler, Dominique, Bakker, Stephan J. L., Beilby, John, Bergman, Richard N., Blangero, John, Brown, Morris J., Burnier, Michel, Campbell, Harry, Chakravarti, Aravinda, Chines, Peter S., Claudi-Boehm, Simone, Collins, Francis S., Crawford, Dana C., Danesh, John, de Faire, Ulf, de Geus, Eco J. C., Dörr, Marcus, Erbel, Raimund, Eriksson, Johan G., Farrall, Martin, Ferrannini, Ele, Ferrières, Jean, Forouhi, Nita G., Forrester, Terrence, Franco, Oscar H., Gansevoort, Ron T., Gieger, Christian, Gudnason, Vilmundur, Haiman, Christopher A., Harris, Tamara B., Hattersley, Andrew T., Heliövaara, Markku, Hicks, Andrew A., Hingorani, Aroon D., Hoffmann, Wolfgang, Hofman, Albert, Homuth, Georg, Humphries, Steve E., Hyppönen, Elina, Illig, Thomas, Jarvelin, Marjo-Riitta, Johansen, Berit, Jousilahti, Pekka, Jula, Antti M., Kaprio, Jaakko, Kee, Frank, Keinanen-Kiukaanniemi, Sirkka M., Kooner, Jaspal S., Kooperberg, Charles, Kovacs, Peter, Kraja, Aldi T., Kumari, Meena, Kuulasmaa, Kari, Kuusisto, Johanna, Lakka, Timo A., Langenberg, Claudia, Le Marchand, Loic, Lehtimäki, Terho, Lyssenko, Valeriya, Männistö, Satu, Marette, André, Matise, Tara C., McKenzie, Colin A., McKnight, Barbara, Musk, Arthur W., Möhlenkamp, Stefan, Morris, Andrew D., Nelis, Mari, Ohlsson, Claes, Oldehinkel, Albertine J., Ong, Ken K., Palmer, Lyle J., Penninx, Brenda W., Peters, Annette, Pramstaller, Peter P., Raitakari, Olli T., Rankinen, Tuomo, Rao, D. C., Rice, Treva K., Ridker, Paul M., Ritchie, Marylyn D., Rudan, Igor, Salomaa, Veikko, Samani, Nilesh J., Saramies, Jouko, Sarzynski, Mark A., Schwarz, Peter E. H., Shuldiner, Alan R., Staessen, Jan A., Steinthorsdottir, Valgerdur, Stolk, Ronald P., Strauch, Konstantin, Tönjes, Anke, Tremblay, Angelo, Tremoli, Elena, Vohl, Marie-Claude, Völker, Uwe, Vollenweider, Peter, Wilson, James F., Witteman, Jacqueline C., Adair, Linda S., Bochud, Murielle, Boehm, Bernhard O., Bornstein, Stefan R., Bouchard, Claude, Cauchi, Stéphane, Caulfield, Mark J., Chambers, John C., Chasman, Daniel I., Cooper, Richard S., Dedoussis, George, Ferrucci, Luigi, Froguel, Philippe, Grabe, Hans-Jörgen, Hamsten, Anders, Hui, Jennie, Hveem, Kristian, Jöckel, Karl-Heinz, Kivimaki, Mika, Kuh, Diana, Laakso, Markku, Liu, Yongmei, März, Winfried, Munroe, Patricia B., Njølstad, Inger, Oostra, Ben A., Palmer, Colin N. A., Pedersen, Nancy L., Perola, Markus, Pérusse, Louis, Peters, Ulrike, Power, Chris, Quertermous, Thomas, Rauramaa, Rainer, Rivadeneira, Fernando, Saaristo, Timo E., Saleheen, Danish, Sinisalo, Juha, Eline Slagboom, P., Snieder, Harold, Spector, Tim D., Thorsteinsdottir, Unnur, Stumvoll, Michael, Tuomilehto, Jaakko, Uitterlinden, André G., Uusitupa, Matti, van der Harst, Pim, Veronesi, Giovanni, Walker, Mark, Wareham, Nicholas J., Watkins, Hugh, Wichmann, H-Erich, Abecasis, Goncalo R., Assimes, Themistocles L., Berndt, Sonja I., Boehnke, Michael, Borecki, Ingrid B., Deloukas, Panos, Franke, Lude, Frayling, Timothy M., Groop, Leif C., Hunter, David J., Kaplan, Robert C., OʼConnell, Jeffrey R., Qi, Lu, Schlessinger, David, Strachan, David P., Stefansson, Kari, van Duijn, Cornelia M., Willer, Cristen J., Visscher, Peter M., Yang, Jian, Hirschhorn, Joel N., Carola Zillikens, M., McCarthy, Mark I., Speliotes, Elizabeth K., North, Kari E., Fox, Caroline S., Barroso, Inês, Franks, Paul W., Ingelsson, Erik, Heid, Iris M., Loos, Ruth J. F., Cupples, Adrienne L., Morris, Andrew P., Lindgren, Cecilia M., and Mohlke, Karen L

Published
2015
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33. 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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40. Genome-wide linkage scan for submaximal exercise heart rate in the HERITAGE family study

Author

Spielmann, Nadine, Leon, Arthur S., Rao, D.C., Rice, Treva, Skinner, James S., Rankinen, Tuomo, and Bouchard, Claude

Subjects
Exercise -- Health aspects, Exercise -- Research, Heart beat -- Genetic aspects, Heart beat -- Measurement, Heart beat -- Research, Human genome -- Research, Biological sciences
Abstract

The purpose of this study was to identify regions of the human genome linked to submaximal exercise heart rates in the sedentary state and in response to a standardized 20-wk endurance training program in blacks and whites of the HERITAGE Family Study. A total of 701 polymorphic markers covering the 22 autosomes were used in the genome-wide linkage scan, with 328 sibling pairs from 99 white nuclear families and 102 pairs from 115 black family units. Steady-state heart rates were measured at the relative intensity of 60% maximal oxygen uptake (HR60) and at the absolute intensity of 50 W (HR50). Baseline phenotypes were adjusted for age, sex, and baseline body mass index (BMI) and training responses (posttraining minus baseline, [DELTA]) were adjusted for age, sex, baseline BMI, and baseline value of the phenotype. Two analytic strategies were used, a multipoint variance components and a regression-based multipoint linkage analysis. In whites, promising linkages (LOD > 1.75) were identified on 18q21-q22 for baseline HR50 (LOD = 2.64; P = 0.0002) and [DELTA]HR60 (LOD = 2.10; P = 0.0009) and on chromosome 2q33.3 for [DELTA]HR50 (LOD = 2.13; P = 0.0009). In blacks, evidence of promising linkage for baseline HR50 was detected with several markers within the chromosomal region 10q24-q25.3 (peak LOD = 2.43, P = 0.0004 with D10S597). The most promising regions for fine mapping in the HERITAGE Family Study were found on 2q33 for HR50 training response in whites, on 10q25-26 for baseline HR60 in blacks, and on 18q21-22 for both baseline HR50 and [DELTA]HR60 in whites. exercise training; linkage; quantitative trait loci; genotype

Published
2007

41. Peroxisome proliferator-activated receptor-[delta] polymorphisms are associated with physical performance and plasma lipids: the HERITAGE Family Study

Author

Hautala, Arto J., Leon, Arthur S., Skinner, James S., Rao, D.C., Bouchard, Claude, and Rankinen, Tuomo

Subjects
Genetic polymorphisms -- Research, Blood lipids -- Research, Blood lipids -- Genetic aspects, Cholesterol, HDL -- Research, Cholesterol, HDL -- Genetic aspects, Exercise -- Physiological aspects, Exercise -- Research, Cardiovascular research, Biological sciences
Abstract

We tested the hypothesis that peroxisome proliferator-activated receptor-[delta] (PPAR[delta]) gene polymorphisms are associated with cardiorespiratory fitness and plasma lipid responses to endurance training. Associations between the PPAR[delta] exon 4 + 15 C/T and exon 7 + 65 A/G polymorphisms and maximal exercise capacity and plasma lipid responses to 20 wk of endurance training were investigated in healthy white (n = 477) and black (n = 264) subjects. In black subjects, the exon 4 + 15 C/C homozygotes showed a smaller training-induced increase in maximal oxygen consumption (P = 0.028) than the C/T and T/T genotypes. Similarly, a lower training response in maximal power output was observed in the exon 4 + 15 C/C homozygotes (P = 0.005) compared with the heterozygotes and the T/T homozygotes in black subjects, and a similar trend was evident in white subjects (P = 0.087). In white subjects, baseline apolipoprotein A-1 (Apo A-1)levels were higher in the exon 4 + 15 C/C (P = 0.011) and exon 7 + 65 G/G (P = 0.05) genotypes compared with those in the other genotypes. In white subjects, exon 4 + 15 C/C (P = 0.0025) and exon 7 + 65 G/G (P = 0.011) genotypes showed significantly greater increases in plasma high-density lipoprotein-cholesterol (HDL-C) levels with endurance training than in the other genotypes, whereas in black subjects the exon 4 + 15 CC homozygotes tended to increase (P = 0.057) their Apo A-1 levels more than the T allele carriers. DNA sequence variation in the PPAR[delta] locus is a potential modifier of changes in cardiorespiratory fitness and plasma HDL-C in healthy individuals in response to regular exercise. cardiorespiratory fitness; high-density lipoprotein cholesterol; exercise training doi:10.1152/ajpheart.01092.2006.

Published
2007

44. Heart rate recovery after maximal exercise is associated with acetylcholine receptor M2 (CHRM2) gene polymorphism

Author

Hautala, Arto J., Rankinen, Tuomo, Kiviniemi, Antti M., Makikallio, Timo H., Huikuri, Heikki V., Bouchard, Claude, and Tulppo, Mikko P.

Subjects
Heart function tests -- Research, Heart beat -- Research, Acetylcholine -- Receptors, Acetylcholine -- Research, Exercise -- Physiological aspects, Exercise -- Research, Biological sciences
Abstract

The determinants of heart rate (HR) recovery after exercise are not well known, although attenuated HR recovery is associated with an increased risk of cardiovascular mortality. Because acetylcholine receptor subtype M2 (CHRM2) plays a key role in the cardiac chronotropic response, we tested the hypothesis that, in healthy individuals, the CHRM2 gene polymorphisms might be associated with HR recovery 1 rain after the termination of a maximal exercise test, both before and after endurance training. The study population consisted of sedentary men and women (n = 95, 42 [+ or -] 5 yr) assigned to a training (n = 80) or control group (n = 15). The study subjects underwent a 2-wk laboratory-controlled endurance training program, which included five 40-min sessions/wk at 70-80% of maximal HR. HR recovery differed between the intron 5 rs324640 genotypes at baseline (C/C, -33 [+ or -] 10; C/T, -33 [+ or -] 7; and T/T, -40 [+ or -] 11 beats/min, P = 0.008). Endurance training further strengthened the association: the less common C/C homozygotes showed 6 and 12 beats/rain lower HR recovery than the C/T heterozygotes or the T/T homozygotes (P = 0.001), respectively. A similar association was found between A/T transversion at the 3'-untranslated region of the CHRM2 gene and HR recovery at baseline (P = 0.025) and after endurance training (P = 0.005). These data suggest that DNA sequence variation at the CHRM2 locus is a potential modifier of HR recovery in the sedentary state and after short-term endurance training in healthy individuals. genotype; exercise training; cardiovascular autonomic function

Published
2006

45. Endurance training-induced changes in insulin sensitivity and gene expression

Author

Teran-Garcia, Margarita, Rankinen, Tuomo, Koza, Robert A., Rao, D.C., and Bouchard, Claude

Subjects
Gene expression -- Research, Insulin -- Research, Insulin -- Physiological aspects, Exercise -- Research, Exercise -- Physiological aspects, Exercise -- Genetic aspects, Biological sciences
Abstract

The beneficial effects of regular physical activity on insulin sensitivity (SO and glucose tolerance are well documented, with considerable heterogeneity in responsiveness to exercise training (ET). To find novel candidate genes for ET-induced improvement in [S.sub.I] we used microarray technology. Total RNA was isolated from vastus lateralis muscle before and after 20 wk of exercise from individuals participating in the HERITAGE Family Study. [S.sub.I] index was derived from a frequently sampled intravenous glucose tolerance test using MINMOD Millennium software. Sixteen subjects were selected: eight showing no changes in [S.sub.I] (low responders, L[S.sub.1]R) and eight displaying marked improvement in [S.sub.I] (high responders, H[S.sub.I]R) with ET. The [S.sub.I] increase was about four times greater in H[S.sub.I]R compared with L[S.sub.I]R (+3.6 [+ or -] 0.5 vs. -1.2 [+ or -] 0.5 [micro]U*[ml.sup.-1] * [min.sup.-1], mean [+ or -] SE), whereas age, body mass index, percent body fat, and baseline [S.sub.I] were similar between the groups. Triplicate microarrays were performed, comparing pooled RNA with H[S.sub.I]R and L[S.sub.I]R individuals for differences in gene expression before and after ET using in situ-generated microarrays (18, 861 genes). Array data were validated by quantitative RT-PCR. Almost twice as many genes showed at least twofold differences between H[S.sub.I]R and L[S.sub.I]R after training compared with pretraining. We identified differentially expressed genes involved in energy metabolism and signaling, novel structural genes, and transcripts of unknown function. Genes of interest upregulated in H[S.sub.I]R include V-Ski oncogene, four-and-a-half LIM domain 1, and titin. Further study of these novel candidate genes should provide a better understanding of molecular mechanisms involved in the improvement in insulin sensitivity in response to regular exercise. microarray; MINMOD Millennium; exercise training

Published
2005

46. Gene-diet interactions on body weight changes

Author

Loos, Ruth J.F. and Rankinen, Tuomo

Subjects
Weight loss -- Case studies, Obesity -- Case studies
Abstract

Obesity is one of the most pressing problems in the industrialized world. The susceptibility to obesity is partly determined by genetic factors, but an "obesity-promoting environment" is typically necessary for its phenotypic expression. Such a genetically mediated susceptibility to environmental exposure is referred to as gene-environment interaction. This article reviews the effect of genotype-diet interactions on body weight and body composition changes. A few well-controlled studies with monozygotic twins have specifically addressed the genetic background of interindividual variation in response to overfeeding or energy restriction. Some individuals will gain or lose weight more easily than others, but subjects sharing the same genotype (monozygotic twins) will respond in a similar way, suggesting that the responsiveness to diet is mediated by their genotype. Further evidence for gene-environment interactions comes from candidate gene studies. Genes involved in pathways regulating energy expenditure and food intake may play a role in the predisposition to obesity. For example, DNA sequence variation in genes encoding the adrenergic receptors and uncoupling proteins are of particular relevance. This growing body of research may help in the development of antiobesity treatments and perhaps genetic tests to predict the risk for obesity. J Am Diet Assoc. 2005;105:S29-S34.

Published
2005

48. Calcium intake is associated with adiposity in Black and White men and White women of the HERITAGE Family Study

Author

Loos, Ruth J.F., Rankinen, Tuomo, Leon, Arthur S., Skinner, James S., Wilmore, Jack H., Rao, D.C., and Bouchard, Claude

Subjects
Adipose tissues -- Research, Calcium, Dietary -- Nutritional aspects, Food/cooking/nutrition
Abstract

Calcium ([Ca.sup.2+]) intake may play a role in the regulation of body weight. Increased [Ca.sup.2+] intake has been associated with lower body weight, BMI, and adiposity measures in cross-sectional studies. We examined the association between [Ca.sup.2+] intake, derived from the Willett FFQ, and overall and abdominal adiposity in Black and White men and women of the HERITAGE Family Study. BMI, the percentage of body fat (%FAT), the sum of 8 skinfold thicknesses, computerized tomography total abdominal fat (TAF), abdominal visceral (AVF) and abdominal subcutaneous (ASF) fat, and waist circumference were measured in 362 men (109 Blacks, 253 Whites) and 462 women (201 Blacks, 261 Whites). Subjects were divided into tertiles of energy-adjusted [Ca.sup.2+] intake. Adiposity measures across tertiles were compared by ANOVA and also regressed against the energy-adjusted [Ca.sup.2+] intake to test for a linear trend. The strongest inverse associations appeared in Black men and White women. Black men in the high [Ca.sup.2+] intake group were leaner than those in the low [Ca.sup.2+] intake group: BMI 23.4 [+ or -] 0.9 vs. 26.7 + 1.1 kg/[m.sup.2] (P = 0.01); for all other adiposity measures, P < 0.05. In White women, regression analyses showed significant inverse associations between [Ca.sup.2+] intake and BMI (P = 0.02), %FAT (P = 0.001), TAF (P = 0.006), AVF (P = 0.03), and ASF (P = 0.01). The percentage of fat of White men in the highest [Ca.sup.2+] intake group was significantly lower than in the lowest [Ca.sup.2+] group (P = 0.04). No significant associations were found in Black women. Low [Ca.sup.2+] intake may be associated with higher adiposity, particularly in men and White women. KEY WORDS: * dietary calcium intake * body composition * adiposity * abdominal fat * HERITAGE Family Study

Published
2004

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