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298 results on '"BOUCHARD, CLAUDE"'

1. Plasma Proteomics of Exercise Blood Pressure and Incident Hypertension

Author: Rao, Prashant, Keyes, Michelle. J., Mi, Michael Y., Barber, Jacob L., Tahir, Usman A., Deng, Shuliang, Clish, Clary B., Shen, Dongxiao, Farrell, Laurie. A., Wilson, James G., Gao, Yan, Yimer, Wondwosen K., Ekunwe, Lynette, Hall, Michael E., Muntner, Paul M., Guo, Xiuqing, Taylor, Kent D., Tracy, Russell P., Rich, Stephen S., Rotter, Jerome I., Xanthakis, Vanessa, Vasan, Ramachandran S., Bouchard, Claude, Sarzynski, Mark A., Gerszten, Robert E., and Robbins, Jeremy M.
Abstract: IMPORTANCE: Blood pressure response during acute exercise (exercise blood pressure [EBP]) is associated with the future risk of hypertension and cardiovascular disease (CVD). Biochemical characterization of EBP could inform disease biology and identify novel biomarkers of future hypertension. OBJECTIVE: To identify protein markers associated with EBP and test their association with incident hypertension. DESIGN, SETTING, AND PARTICIPANTS: This study assayed 4977 plasma proteins in 681 healthy participants (from 763 assessed) of the Health, Risk Factors, Exercise Training and Genetics (HERITAGE; data collection from January 1993 to December 1997 and plasma proteomics from January 2019 to January 2020) Family Study at rest who underwent 2 cardiopulmonary exercise tests. Individuals were free of CVD at the time of recruitment. Individuals with resting SBP ≥160 mm Hg or DBP ≥100 mm Hg or taking antihypertensive drug therapy were excluded from the study. The association between resting plasma protein levels to both resting BP and EBP was evaluated. Proteins associated with EBP were analyzed for their association with incident hypertension in the Framingham Heart Study (FHS; n = 1177) and validated in the Jackson Heart Study (JHS; n = 772) and Multi-Ethnic Study of Atherosclerosis (MESA; n = 1367). Proteins associated with incident hypertension were tested for putative causal links in approximately 700 000 individuals using cis-protein quantitative loci mendelian randomization (cis-MR). Data were analyzed from January 2023 to January 2024. EXPOSURES: Plasma proteins. MAIN OUTCOMES AND MEASURES: EBP was defined as the BP response during a fixed workload (50 W) on a cycle ergometer. Hypertension was defined as BP ≥140/90 mm Hg or taking antihypertensive medication. RESULTS: Among the 681 participants in the HERITAGE Family Study, the mean (SD) age was 34 (13) years; 366 participants (54%) were female; 238 (35%) were self-reported Black and 443 (65%) were self-reported White. Proteomic profiling of EBP revealed 34 proteins that would not have otherwise been identified through profiling of resting BP alone. Transforming growth factor β receptor 3 (TGFBR3) and prostaglandin D2 synthase (PTGDS) had the strongest association with exercise systolic BP (SBP) and diastolic BP (DBP), respectively (TGFBR3: exercise SBP, β estimate, −3.39; 95% CI, −4.79 to −2.00; P = 2.33 × 10−6; PTGDS: exercise DBP β estimate, −2.50; 95% CI, −3.29 to −1.70; P = 1.18 × 10−9). In fully adjusted models, TGFBR3 was inversely associated with incident hypertension in FHS, JHS, and MESA (hazard ratio [HR]: FHS, 0.86; 95% CI, 0.75-0.97; P = .01; JHS, 0.87; 95% CI, 0.77-0.97; P = .02; MESA, 0.84; 95% CI, 0.71-0.98; P = .03; pooled cohort, 0.86; 95% CI, 0.79-0.92; P = 6 × 10−5). Using cis-MR, genetically predicted levels of TGFBR3 were associated with SBP, hypertension, and CVD events (SBP: β, −0.38; 95% CI, −0.64 to −0.11; P = .006; hypertension: odds ratio [OR], 0.99; 95% CI, 0.98-0.99; P < .001; heart failure with hypertension: OR, 0.86; 95% CI, 0.77-0.97; P = .01; CVD: OR, 0.84; 95% CI, 0.77-0.92; P = 8 × 10−5; cerebrovascular events: OR, 0.77; 95% CI, 0.70-0.85; P = 5 × 10−7). CONCLUSIONS AND RELEVANCE: Plasma proteomic profiling of EBP identified a novel protein, TGFBR3, which may protect against elevated BP and long-term CVD outcomes.
Published: 2024
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2. Proteomic analysis of cardiorespiratory fitness for prediction of mortality and multisystem disease risks

Author: Perry, Andrew S., Farber-Eger, Eric, Gonzales, Tomas, Tanaka, Toshiko, Robbins, Jeremy M., Murthy, Venkatesh L., Stolze, Lindsey K., Zhao, Shilin, Huang, Shi, Colangelo, Laura A., Deng, Shuliang, Hou, Lifang, Lloyd-Jones, Donald M., Walker, Keenan A., Ferrucci, Luigi, Watts, Eleanor L., Barber, Jacob L., Rao, Prashant, Mi, Michael Y., Gabriel, Kelley Pettee, Hornikel, Bjoern, Sidney, Stephen, Houstis, Nicholas, Lewis, Gregory D., Liu, Gabrielle Y., Thyagarajan, Bharat, Khan, Sadiya S., Choi, Bina, Washko, George, Kalhan, Ravi, Wareham, Nick, Bouchard, Claude, Sarzynski, Mark A., Gerszten, Robert E., Brage, Soren, Wells, Quinn S., Nayor, Matthew, and Shah, Ravi V.
Abstract: Despite the wide effects of cardiorespiratory fitness (CRF) on metabolic, cardiovascular, pulmonary and neurological health, challenges in the feasibility and reproducibility of CRF measurements have impeded its use for clinical decision-making. Here we link proteomic profiles to CRF in 14,145 individuals across four international cohorts with diverse CRF ascertainment methods to establish, validate and characterize a proteomic CRF score. In a cohort of around 22,000 individuals in the UK Biobank, a proteomic CRF score was associated with a reduced risk of all-cause mortality (unadjusted hazard ratio 0.50 (95% confidence interval 0.48–0.52) per 1 s.d. increase). The proteomic CRF score was also associated with multisystem disease risk and provided risk reclassification and discrimination beyond clinical risk factors, as well as modulating high polygenic risk of certain diseases. Finally, we observed dynamicity of the proteomic CRF score in individuals who undertook a 20-week exercise training program and an association of the score with the degree of the effect of training on CRF, suggesting potential use of the score for personalization of exercise recommendations. These results indicate that population-based proteomics provides biologically relevant molecular readouts of CRF that are additive to genetic risk, potentially modifiable and clinically translatable.
Published: 2024
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3. 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, R. J., 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., Zheng, Wei, Palmer, Lyle J., Lehtimäki, Terho, Gudnason, Vilmundur, Morrison, Alanna C., Pereira, Alexandre C., Fornage, Myriam, Psaty, Bruce M., van Duijn, Cornelia M., Liu, Ching-Ti, Kelly, Tanika N., Evans, Michele K., Bouchard, Claude, Fox, Ervin R., Kooperberg, Charles, Zhu, Xiaofeng, Lakka, Timo A., Esko, Tõnu, North, Kari E., Deary, Ian J., Snieder, Harold, Penninx, Brenda W. J. H., Gauderman, W. James, Rao, Dabeeru C., Redline, Susan, and van Heemst, Diana
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< 5 × 10−8), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (Pint< 5 × 10−8). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (Pint= 2 × 10−6). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1and RGL3/ELAVL3previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (Pint< 10−3). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep–wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
Published: 2024
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4. 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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5. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

Author: Wang, Zhe, Emmerich, Andrew, Pillon, Nicolas J., Moore, Tim, Hemerich, Daiane, Cornelis, Marilyn C., Mazzaferro, Eugenia, Broos, Siacia, Ahluwalia, Tarunveer S., Bartz, Traci M., Bentley, Amy R., Bielak, Lawrence F., Chong, Mike, Chu, Audrey Y., Berry, Diane, Dorajoo, Rajkumar, Dueker, Nicole D., Kasbohm, Elisa, Feenstra, Bjarke, Feitosa, Mary F., Gieger, Christian, Graff, Mariaelisa, Hall, Leanne M., Haller, Toomas, Hartwig, Fernando P., Hillis, David A., Huikari, Ville, Heard-Costa, Nancy, Holzapfel, Christina, Jackson, Anne U., Johansson, Åsa, Jørgensen, Anja Moltke, Kaakinen, Marika A., Karlsson, Robert, Kerr, Kathleen F., Kim, Boram, Koolhaas, Chantal M., Kutalik, Zoltan, Lagou, Vasiliki, Lind, Penelope A., Lorentzon, Mattias, Lyytikäinen, Leo-Pekka, Mangino, Massimo, Metzendorf, Christoph, Monroe, Kristine R., Pacolet, Alexander, Pérusse, Louis, Pool, Rene, Richmond, Rebecca C., Rivera, Natalia V., Robiou-du-Pont, Sebastien, Schraut, Katharina E., Schulz, Christina-Alexandra, Stringham, Heather M., Tanaka, Toshiko, Teumer, Alexander, Turman, Constance, van der Most, Peter J., Vanmunster, Mathias, van Rooij, Frank J. A., van Vliet-Ostaptchouk, Jana V., Zhang, Xiaoshuai, Zhao, Jing-Hua, Zhao, Wei, Balkhiyarova, Zhanna, Balslev-Harder, Marie N., Baumeister, Sebastian E., Beilby, John, Blangero, John, Boomsma, Dorret I., Brage, Soren, Braund, Peter S., Brody, Jennifer A., Bruinenberg, Marcel, Ekelund, Ulf, Liu, Ching-Ti, Cole, John W., Collins, Francis S., Cupples, L. Adrienne, Esko, Tõnu, Enroth, Stefan, Faul, Jessica D., Fernandez-Rhodes, Lindsay, Fohner, Alison E., Franco, Oscar H., Galesloot, Tessel E., Gordon, Scott D., Grarup, Niels, Hartman, Catharina A., Heiss, Gerardo, Hui, Jennie, Illig, Thomas, Jago, Russell, James, Alan, Joshi, Peter K., Jung, Taeyeong, Kähönen, Mika, Kilpeläinen, Tuomas O., Koh, Woon-Puay, Kolcic, Ivana, Kraft, Peter P., Kuusisto, Johanna, Launer, Lenore J., Li, Aihua, Linneberg, Allan, Luan, Jian’an, Vidal, Pedro Marques, Medland, Sarah E., Milaneschi, Yuri, Moscati, Arden, Musk, Bill, Nelson, Christopher P., Nolte, Ilja M., Pedersen, Nancy L., Peters, Annette, Peyser, Patricia A., Power, Christine, Raitakari, Olli T., Reedik, Mägi, Reiner, Alex P., Ridker, Paul M., Rudan, Igor, Ryan, Kathy, Sarzynski, Mark A., Scott, Laura J., Scott, Robert A., Sidney, Stephen, Siggeirsdottir, Kristin, Smith, Albert V., Smith, Jennifer A., Sonestedt, Emily, Strøm, Marin, Tai, E. Shyong, Teo, Koon K., Thorand, Barbara, Tönjes, Anke, Tremblay, Angelo, Uitterlinden, Andre G., Vangipurapu, Jagadish, van Schoor, Natasja, Völker, Uwe, Willemsen, Gonneke, Williams, Kayleen, Wong, Quenna, Xu, Huichun, Young, Kristin L., Yuan, Jian Min, Zillikens, M. Carola, Zonderman, Alan B., Ameur, Adam, Bandinelli, Stefania, Bis, Joshua C., Boehnke, Michael, Bouchard, Claude, Chasman, Daniel I., Smith, George Davey, de Geus, Eco J. C., Deldicque, Louise, Dörr, Marcus, Evans, Michele K., Ferrucci, Luigi, Fornage, Myriam, Fox, Caroline, Garland, Theodore, Gudnason, Vilmundur, Gyllensten, Ulf, Hansen, Torben, Hayward, Caroline, Horta, Bernardo L., Hyppönen, Elina, Jarvelin, Marjo-Riitta, Johnson, W. Craig, Kardia, Sharon L. R., Kiemeney, Lambertus A., Laakso, Markku, Langenberg, Claudia, Lehtimäki, Terho, Marchand, Loic Le, Magnusson, Patrik K. E., Martin, Nicholas G., Melbye, Mads, Metspalu, Andres, Meyre, David, North, Kari E., Ohlsson, Claes, Oldehinkel, Albertine J., Orho-Melander, Marju, Pare, Guillaume, Park, Taesung, Pedersen, Oluf, Penninx, Brenda W. J. H., Pers, Tune H., Polasek, Ozren, Prokopenko, Inga, Rotimi, Charles N., Samani, Nilesh J., Sim, Xueling, Snieder, Harold, Sørensen, Thorkild I. A., Spector, Tim D., Timpson, Nicholas J., van Dam, Rob M., van der Velde, Nathalie, van Duijn, Cornelia M., Vollenweider, Peter, Völzke, Henry, Voortman, Trudy, Waeber, Gérard, Wareham, Nicholas J., Weir, David R., Wichmann, Heinz-Erich, Wilson, James F., Hevener, Andrea L., Krook, Anna, Zierath, Juleen R., Thomis, Martine A. I., Loos, Ruth J. F., and Hoed, Marcel den
Abstract: Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIAmuscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.
Published: 2022
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6. The study of human variability became a passion

Author: Bouchard, Claude
Published: 2022
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7. Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease

Author: Katz, Daniel H., Tahir, Usman A., Bick, Alexander G., Pampana, Akhil, Ngo, Debby, Benson, Mark D., Yu, Zhi, Robbins, Jeremy M., Chen, Zsu-Zsu, Cruz, Daniel E., Deng, Shuliang, Farrell, Laurie, Sinha, Sumita, Schmaier, Alec A., Shen, Dongxiao, Gao, Yan, Hall, Michael E., Correa, Adolfo, Tracy, Russell P., Durda, Peter, Taylor, Kent D., Liu, Yongmei, Johnson, W. Craig, Guo, Xiuqing, Yao, Jie, Ida Chen, Yii-Der, Manichaikul, Ani W., Jain, Deepti, Bouchard, Claude, Sarzynski, Mark A., Rich, Stephen S., Rotter, Jerome I., Wang, Thomas J., Wilson, James G., Natarajan, Pradeep, and Gerszten, Robert E.
Abstract: Supplemental Digital Content is available in the text.
Published: 2022
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8. A saturated map of common genetic variants associated with human height

Author: Yengo, Loïc, Vedantam, Sailaja, Marouli, Eirini, Sidorenko, Julia, Bartell, Eric, Sakaue, Saori, Graff, Marielisa, Eliasen, Anders U., Jiang, Yunxuan, Raghavan, Sridharan, Miao, Jenkai, Arias, Joshua D., Graham, Sarah E., Mukamel, Ronen E., Spracklen, Cassandra N., Yin, Xianyong, Chen, Shyh-Huei, Ferreira, Teresa, Highland, Heather H., Ji, Yingjie, Karaderi, Tugce, Lin, Kuang, Lüll, Kreete, Malden, Deborah E., Medina-Gomez, Carolina, Machado, Moara, Moore, Amy, Rüeger, Sina, Sim, Xueling, Vrieze, Scott, Ahluwalia, Tarunveer S., Akiyama, Masato, Allison, Matthew A., Alvarez, Marcus, Andersen, Mette K., Ani, Alireza, Appadurai, Vivek, Arbeeva, Liubov, Bhaskar, Seema, Bielak, Lawrence F., Bollepalli, Sailalitha, Bonnycastle, Lori L., Bork-Jensen, Jette, Bradfield, Jonathan P., Bradford, Yuki, Braund, Peter S., Brody, Jennifer A., Burgdorf, Kristoffer S., Cade, Brian E., Cai, Hui, Cai, Qiuyin, Campbell, Archie, Cañadas-Garre, Marisa, Catamo, Eulalia, Chai, Jin-Fang, Chai, Xiaoran, Chang, Li-Ching, Chang, Yi-Cheng, Chen, Chien-Hsiun, Chesi, Alessandra, Choi, Seung Hoan, Chung, Ren-Hua, Cocca, Massimiliano, Concas, Maria Pina, Couture, Christian, Cuellar-Partida, Gabriel, Danning, Rebecca, Daw, E. Warwick, Degenhard, Frauke, Delgado, Graciela E., Delitala, Alessandro, Demirkan, Ayse, Deng, Xuan, Devineni, Poornima, Dietl, Alexander, Dimitriou, Maria, Dimitrov, Latchezar, Dorajoo, Rajkumar, Ekici, Arif B., Engmann, Jorgen E., Fairhurst-Hunter, Zammy, Farmaki, Aliki-Eleni, Faul, Jessica D., Fernandez-Lopez, Juan-Carlos, Forer, Lukas, Francescatto, Margherita, Freitag-Wolf, Sandra, Fuchsberger, Christian, Galesloot, Tessel E., Gao, Yan, Gao, Zishan, Geller, Frank, Giannakopoulou, Olga, Giulianini, Franco, Gjesing, Anette P., Goel, Anuj, Gordon, Scott D., Gorski, Mathias, Grove, Jakob, Guo, Xiuqing, Gustafsson, Stefan, Haessler, Jeffrey, Hansen, Thomas F., Havulinna, Aki S., Haworth, Simon J., He, Jing, Heard-Costa, Nancy, Hebbar, Prashantha, Hindy, George, Ho, Yuk-Lam A., Hofer, Edith, Holliday, Elizabeth, Horn, Katrin, Hornsby, Whitney E., Hottenga, Jouke-Jan, Huang, Hongyan, Huang, Jie, Huerta-Chagoya, Alicia, Huffman, Jennifer E., Hung, Yi-Jen, Huo, Shaofeng, Hwang, Mi Yeong, Iha, Hiroyuki, Ikeda, Daisuke D., Isono, Masato, Jackson, Anne U., Jäger, Susanne, Jansen, Iris E., Johansson, Ingegerd, Jonas, Jost B., Jonsson, Anna, Jørgensen, Torben, Kalafati, Ioanna-Panagiota, Kanai, Masahiro, Kanoni, Stavroula, Kårhus, Line L., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kawaguchi, Takahisa, Kember, Rachel L., Kentistou, Katherine A., Kim, Han-Na, Kim, Young Jin, Kleber, Marcus E., Knol, Maria J., Kurbasic, Azra, Lauzon, Marie, Le, Phuong, Lea, Rodney, Lee, Jong-Young, Leonard, Hampton L., Li, Shengchao A., Li, Xiaohui, Li, Xiaoyin, Liang, Jingjing, Lin, Honghuang, Lin, Shih-Yi, Liu, Jun, Liu, Xueping, Lo, Ken Sin, Long, Jirong, Lores-Motta, Laura, Luan, Jian’an, Lyssenko, Valeriya, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamakou, Vasiliki, Mangino, Massimo, Manichaikul, Ani, Marten, Jonathan, Mattheisen, Manuel, Mavarani, Laven, McDaid, Aaron F., Meidtner, Karina, Melendez, Tori L., Mercader, Josep M., Milaneschi, Yuri, Miller, Jason E., Millwood, Iona Y., Mishra, Pashupati P., Mitchell, Ruth E., Møllehave, Line T., Morgan, Anna, Mucha, Soeren, Munz, Matthias, Nakatochi, Masahiro, Nelson, Christopher P., Nethander, Maria, Nho, Chu Won, Nielsen, Aneta A., Nolte, Ilja M., Nongmaithem, Suraj S., Noordam, Raymond, Ntalla, Ioanna, Nutile, Teresa, Pandit, Anita, Christofidou, Paraskevi, Pärna, Katri, Pauper, Marc, Petersen, Eva R. B., Petersen, Liselotte V., Pitkänen, Niina, Polašek, Ozren, Poveda, Alaitz, Preuss, Michael H., Pyarajan, Saiju, Raffield, Laura M., Rakugi, Hiromi, Ramirez, Julia, Rasheed, Asif, Raven, Dennis, Rayner, Nigel W., Riveros, Carlos, Rohde, Rebecca, Ruggiero, Daniela, Ruotsalainen, Sanni E., Ryan, Kathleen A., Sabater-Lleal, Maria, Saxena, Richa, Scholz, Markus, Sendamarai, Anoop, Shen, Botong, Shi, Jingchunzi, Shin, Jae Hun, Sidore, Carlo, Sitlani, Colleen M., Slieker, Roderick C., Smit, Roelof A. J., Smith, Albert V., Smith, Jennifer A., Smyth, Laura J., Southam, Lorraine, Steinthorsdottir, Valgerdur, Sun, Liang, Takeuchi, Fumihiko, Tallapragada, Divya Sri Priyanka, Taylor, Kent D., Tayo, Bamidele O., Tcheandjieu, Catherine, Terzikhan, Natalie, Tesolin, Paola, Teumer, Alexander, Theusch, Elizabeth, Thompson, Deborah J., Thorleifsson, Gudmar, Timmers, Paul R. H. J., Trompet, Stella, Turman, Constance, Vaccargiu, Simona, van der Laan, Sander W., van der Most, Peter J., van Klinken, Jan B., van Setten, Jessica, Verma, Shefali S., Verweij, Niek, Veturi, Yogasudha, Wang, Carol A., Wang, Chaolong, Wang, Lihua, Wang, Zhe, Warren, Helen R., Bin Wei, Wen, Wickremasinghe, Ananda R., Wielscher, Matthias, Wiggins, Kerri L., Winsvold, Bendik S., Wong, Andrew, Wu, Yang, Wuttke, Matthias, Xia, Rui, Xie, Tian, Yamamoto, Ken, Yang, Jingyun, Yao, Jie, Young, Hannah, Yousri, Noha A., Yu, Lei, Zeng, Lingyao, Zhang, Weihua, Zhang, Xinyuan, Zhao, Jing-Hua, Zhao, Wei, Zhou, Wei, Zimmermann, Martina E., Zoledziewska, Magdalena, Adair, Linda S., Adams, Hieab H. H., Aguilar-Salinas, Carlos A., Al-Mulla, Fahd, Arnett, Donna K., Asselbergs, Folkert W., Åsvold, Bjørn Olav, Attia, John, Banas, Bernhard, Bandinelli, Stefania, Bennett, David A., Bergler, Tobias, Bharadwaj, Dwaipayan, Biino, Ginevra, Bisgaard, Hans, Boerwinkle, Eric, Böger, Carsten A., Bønnelykke, Klaus, Boomsma, Dorret I., Børglum, Anders D., Borja, Judith B., Bouchard, Claude, Bowden, Donald W., Brandslund, Ivan, Brumpton, Ben, Buring, Julie E., Caulfield, Mark J., Chambers, John C., Chandak, Giriraj R., Chanock, Stephen J., Chaturvedi, Nish, Chen, Yii-Der Ida, Chen, Zhengming, Cheng, Ching-Yu, Christophersen, Ingrid E., Ciullo, Marina, Cole, John W., Collins, Francis S., Cooper, Richard S., Cruz, Miguel, Cucca, Francesco, Cupples, L. Adrienne, Cutler, Michael J., Damrauer, Scott M., Dantoft, Thomas M., de Borst, Gert J., de Groot, Lisette C. P. G. M., De Jager, Philip L., de Kleijn, Dominique P. V., Janaka de Silva, H., Dedoussis, George V., den Hollander, Anneke I., Du, Shufa, Easton, Douglas F., Elders, Petra J. M., Eliassen, A. Heather, Ellinor, Patrick T., Elmståhl, Sölve, Erdmann, Jeanette, Evans, Michele K., Fatkin, Diane, Feenstra, Bjarke, Feitosa, Mary F., Ferrucci, Luigi, Ford, Ian, Fornage, Myriam, Franke, Andre, Franks, Paul W., Freedman, Barry I., Gasparini, Paolo, Gieger, Christian, Girotto, Giorgia, Goddard, Michael E., Golightly, Yvonne M., Gonzalez-Villalpando, Clicerio, Gordon-Larsen, Penny, Grallert, Harald, Grant, Struan F. A., Grarup, Niels, Griffiths, Lyn, Gudnason, Vilmundur, Haiman, Christopher, Hakonarson, Hakon, Hansen, Torben, Hartman, Catharina A., Hattersley, Andrew T., Hayward, Caroline, Heckbert, Susan R., Heng, Chew-Kiat, Hengstenberg, Christian, Hewitt, Alex W., Hishigaki, Haretsugu, Hoyng, Carel B., Huang, Paul L., Huang, Wei, Hunt, Steven C., Hveem, Kristian, Hyppönen, Elina, Iacono, William G., Ichihara, Sahoko, Ikram, M. Arfan, Isasi, Carmen R., Jackson, Rebecca D., Jarvelin, Marjo-Riitta, Jin, Zi-Bing, Jöckel, Karl-Heinz, Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Kähönen, Mika, Kamatani, Yoichiro, Kang, Kui Dong, Kaprio, Jaakko, Kardia, Sharon L. R., Karpe, Fredrik, Kato, Norihiro, Kee, Frank, Kessler, Thorsten, Khera, Amit V., Khor, Chiea Chuen, Kiemeney, Lambertus A. L. M., Kim, Bong-Jo, Kim, Eung Kweon, Kim, Hyung-Lae, Kirchhof, Paulus, Kivimaki, Mika, Koh, Woon-Puay, Koistinen, Heikki A., Kolovou, Genovefa D., Kooner, Jaspal S., Kooperberg, Charles, Köttgen, Anna, Kovacs, Peter, Kraaijeveld, Adriaan, Kraft, Peter, Krauss, Ronald M., Kumari, Meena, Kutalik, Zoltan, Laakso, Markku, Lange, Leslie A., Langenberg, Claudia, Launer, Lenore J., Le Marchand, Loic, Lee, Hyejin, Lee, Nanette R., Lehtimäki, Terho, Li, Huaixing, Li, Liming, Lieb, Wolfgang, Lin, Xu, Lind, Lars, Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Loeffler, Markus, London, Barry, Lubitz, Steven A., Lye, Stephen J., Mackey, David A., Mägi, Reedik, Magnusson, Patrik K. E., Marcus, Gregory M., Vidal, Pedro Marques, Martin, Nicholas G., März, Winfried, Matsuda, Fumihiko, McGarrah, Robert W., McGue, Matt, McKnight, Amy Jayne, Medland, Sarah E., Mellström, Dan, Metspalu, Andres, Mitchell, Braxton D., Mitchell, Paul, Mook-Kanamori, Dennis O., Morris, Andrew D., Mucci, Lorelei A., Munroe, Patricia B., Nalls, Mike A., Nazarian, Saman, Nelson, Amanda E., Neville, Matt J., Newton-Cheh, Christopher, Nielsen, Christopher S., Nöthen, Markus M., Ohlsson, Claes, Oldehinkel, Albertine J., Orozco, Lorena, Pahkala, Katja, Pajukanta, Päivi, Palmer, Colin N. A., Parra, Esteban J., Pattaro, Cristian, Pedersen, Oluf, Pennell, Craig E., Penninx, Brenda W. J. H., Perusse, Louis, Peters, Annette, Peyser, Patricia A., Porteous, David J., Posthuma, Danielle, Power, Chris, Pramstaller, Peter P., Province, Michael A., Qi, Qibin, Qu, Jia, Rader, Daniel J., Raitakari, Olli T., Ralhan, Sarju, Rallidis, Loukianos S., Rao, Dabeeru C., Redline, Susan, Reilly, Dermot F., Reiner, Alexander P., Rhee, Sang Youl, Ridker, Paul M., Rienstra, Michiel, Ripatti, Samuli, Ritchie, Marylyn D., Roden, Dan M., Rosendaal, Frits R., Rotter, Jerome I., Rudan, Igor, Rutters, Femke, Sabanayagam, Charumathi, Saleheen, Danish, Salomaa, Veikko, Samani, Nilesh J., Sanghera, Dharambir K., Sattar, Naveed, Schmidt, Börge, Schmidt, Helena, Schmidt, Reinhold, Schulze, Matthias B., Schunkert, Heribert, Scott, Laura J., Scott, Rodney J., Sever, Peter, Shiroma, Eric J., Shoemaker, M. Benjamin, Shu, Xiao-Ou, Simonsick, Eleanor M., Sims, Mario, Singh, Jai Rup, Singleton, Andrew B., Sinner, Moritz F., Smith, J. Gustav, Snieder, Harold, Spector, Tim D., Stampfer, Meir J., Stark, Klaus J., Strachan, David P., ‘t Hart, Leen M., Tabara, Yasuharu, Tang, Hua, Tardif, Jean-Claude, Thanaraj, Thangavel A., Timpson, Nicholas J., Tönjes, Anke, Tremblay, Angelo, Tuomi, Tiinamaija, Tuomilehto, Jaakko, Tusié-Luna, Maria-Teresa, Uitterlinden, Andre G., van Dam, Rob M., van der Harst, Pim, Van der Velde, Nathalie, van Duijn, Cornelia M., van Schoor, Natasja M., Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Völzke, Henry, Wacher-Rodarte, Niels H., Walker, Mark, Wang, Ya Xing, Wareham, Nicholas J., Watanabe, Richard M., Watkins, Hugh, Weir, David R., Werge, Thomas M., Widen, Elisabeth, Wilkens, Lynne R., Willemsen, Gonneke, Willett, Walter C., Wilson, James F., Wong, Tien-Yin, Woo, Jeong-Taek, Wright, Alan F., Wu, Jer-Yuarn, Xu, Huichun, Yajnik, Chittaranjan S., Yokota, Mitsuhiro, Yuan, Jian-Min, Zeggini, Eleftheria, Zemel, Babette S., Zheng, Wei, Zhu, Xiaofeng, Zmuda, Joseph M., Zonderman, Alan B., Zwart, John-Anker, Chasman, Daniel I., Cho, Yoon Shin, Heid, Iris M., McCarthy, Mark I., Ng, Maggie C. Y., O’Donnell, Christopher J., Rivadeneira, Fernando, Thorsteinsdottir, Unnur, Sun, Yan V., Tai, E. Shyong, Boehnke, Michael, Deloukas, Panos, Justice, Anne E., Lindgren, Cecilia M., Loos, Ruth J. F., Mohlke, Karen L., North, Kari E., Stefansson, Kari, Walters, Robin G., Winkler, Thomas W., Young, Kristin L., Loh, Po-Ru, Yang, Jian, Esko, Tõnu, Assimes, Themistocles L., Auton, Adam, Abecasis, Goncalo R., Willer, Cristen J., Locke, Adam E., Berndt, Sonja I., Lettre, Guillaume, Frayling, Timothy M., Okada, Yukinori, Wood, Andrew R., Visscher, Peter M., and Hirschhorn, Joel N.
Abstract: Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10–20% (14–24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.
Published: 2022
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9. Regular exercise and patterns of response across multiple cardiometabolic traits: the HERITAGE family study

Author: Barber, Jacob L, Ruiz-Ramie, Jonathan J, Robbins, Jeremy M, Gerszten, Robert E, Leon, Arthur S, Rao, DC, Skinner, James S, Bouchard, Claude, and Sarzynski, Mark A
Abstract: ObjectivesWe investigated whether high responsiveness or low responsiveness to exercise training aggregates in the same individuals across seven cardiometabolic traits.MethodsA total of 564 adults (29.2% black, 53.7% female) from the HERITAGE family study completed a 20-week endurance training programme (at 55%–75% of participants’ maximal oxygen uptake (VO2max)) with VO2max, per cent body fat, visceral adipose tissue, fasting levels of insulin, high-density lipoprotein cholesterol, small low-density lipoprotein particles and inflammatory marker GlycA measured before and after training. For each exercise response trait, we created ethnicity-specific, sex-specific and generation-specific quintiles. High responses were defined as those within the 20th percentile representing the favourable end of the response trait distribution, low responses were defined as the 20th percentile from the least favourable end, and the remaining were labelled as average responses.ResultsOnly one individual had universally high or low responses for all seven cardiometabolic traits. Almost half (49%) of the cohort had at least one high response and one low response across the seven traits. About 24% had at least one high response but no low responses, 24% had one or more low responses but no high responses, and 2.5% had average responses across all traits.ConclusionsInterindividual variation in exercise responses was evident in all the traits we investigated, and responsiveness did not aggregate consistently in the same individuals. While adherence to an exercise prescription is known to produce health benefits, targeted risk factors may not improve.
Published: 2022
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10. The power of genetic diversity in genome-wide association studies of lipids

Author: Graham, Sarah E., Clarke, Shoa L., Wu, Kuan-Han H., Kanoni, Stavroula, Zajac, Greg J. M., Ramdas, Shweta, Surakka, Ida, Ntalla, Ioanna, Vedantam, Sailaja, Winkler, Thomas W., Locke, Adam E., Marouli, Eirini, Hwang, Mi Yeong, Han, Sohee, Narita, Akira, Choudhury, Ananyo, Bentley, Amy R., Ekoru, Kenneth, Verma, Anurag, Trivedi, Bhavi, Martin, Hilary C., Hunt, Karen A., Hui, Qin, Klarin, Derek, Zhu, Xiang, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F., Holm, Hilma, Olafsson, Isleifur, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M., Rasheed, Humaira, Ruotsalainen, Sanni E., Havulinna, Aki S., Veturi, Yogasudha, Feng, QiPing, Rosenthal, Elisabeth A., Lingren, Todd, Pacheco, Jennifer Allen, Pendergrass, Sarah A., Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E., Campbell, Archie, Lin, Kuang, Millwood, Iona Y., Hindy, George, Rasheed, Asif, Faul, Jessica D., Zhao, Wei, Weir, David R., Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Mahajan, Anubha, Brown, Michael R., Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M., Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian’an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Willemsen, Gonneke, Wood, Andrew R., Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E., Chai, Jin Fang, Aadahl, Mette, Yao, Jie, Manichaikul, Ani, Warren, Helen R., Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L., Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Sidore, Carlo, Fiorillo, Edoardo, McDaid, Aaron F., Marques-Vidal, Pedro, Wielscher, Matthias, Trompet, Stella, Sattar, Naveed, Møllehave, Line T., Thuesen, Betina H., Munz, Matthias, Zeng, Lingyao, Huang, Jianfeng, Yang, Bin, Poveda, Alaitz, Kurbasic, Azra, Lamina, Claudia, Forer, Lukas, Scholz, Markus, Galesloot, Tessel E., Bradfield, Jonathan P., Daw, E. Warwick, Zmuda, Joseph M., Mitchell, Jonathan S., Fuchsberger, Christian, Christensen, Henry, Brody, Jennifer A., Feitosa, Mary F., Wojczynski, Mary K., Preuss, Michael, Mangino, Massimo, Christofidou, Paraskevi, Verweij, Niek, Benjamins, Jan W., Engmann, Jorgen, Kember, Rachel L., Slieker, Roderick C., Lo, Ken Sin, Zilhao, Nuno R., Le, Phuong, Kleber, Marcus E., Delgado, Graciela E., Huo, Shaofeng, Ikeda, Daisuke D., Iha, Hiroyuki, Yang, Jian, Liu, Jun, Leonard, Hampton L., Marten, Jonathan, Schmidt, Börge, Arendt, Marina, Smyth, Laura J., Cañadas-Garre, Marisa, Wang, Chaolong, Nakatochi, Masahiro, Wong, Andrew, Hutri-Kähönen, Nina, Sim, Xueling, Xia, Rui, Huerta-Chagoya, Alicia, Fernandez-Lopez, Juan Carlos, Lyssenko, Valeriya, Ahmed, Meraj, Jackson, Anne U., Yousri, Noha A., Irvin, Marguerite R., Oldmeadow, Christopher, Kim, Han-Na, Ryu, Seungho, Timmers, Paul R. H. J., Arbeeva, Liubov, Dorajoo, Rajkumar, Lange, Leslie A., Chai, Xiaoran, Prasad, Gauri, Lorés-Motta, Laura, Pauper, Marc, Long, Jirong, Li, Xiaohui, Theusch, Elizabeth, Takeuchi, Fumihiko, Spracklen, Cassandra N., Loukola, Anu, Bollepalli, Sailalitha, Warner, Sophie C., Wang, Ya Xing, Wei, Wen B., Nutile, Teresa, Ruggiero, Daniela, Sung, Yun Ju, Hung, Yi-Jen, Chen, Shufeng, Liu, Fangchao, Yang, Jingyun, Kentistou, Katherine A., Gorski, Mathias, Brumat, Marco, Meidtner, Karina, Bielak, Lawrence F., Smith, Jennifer A., Hebbar, Prashantha, Farmaki, Aliki-Eleni, Hofer, Edith, Lin, Maoxuan, Xue, Chao, Zhang, Jifeng, Concas, Maria Pina, Vaccargiu, Simona, van der Most, Peter J., Pitkänen, Niina, Cade, Brian E., Lee, Jiwon, van der Laan, Sander W., Chitrala, Kumaraswamy Naidu, Weiss, Stefan, Zimmermann, Martina E., Lee, Jong Young, Choi, Hyeok Sun, Nethander, Maria, Freitag-Wolf, Sandra, Southam, Lorraine, Rayner, Nigel W., Wang, Carol A., Lin, Shih-Yi, Wang, Jun-Sing, Couture, Christian, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Cuellar-Partida, Gabriel, Vestergaard, Henrik, Hildalgo, Bertha, Giannakopoulou, Olga, Cai, Qiuyin, Obura, Morgan O., van Setten, Jessica, Li, Xiaoyin, Schwander, Karen, Terzikhan, Natalie, Shin, Jae Hun, Jackson, Rebecca D., Reiner, Alexander P., Martin, Lisa Warsinger, Chen, Zhengming, Li, Liming, Highland, Heather M., Young, Kristin L., Kawaguchi, Takahisa, Thiery, Joachim, Bis, Joshua C., Nadkarni, Girish N., Launer, Lenore J., Li, Huaixing, Nalls, Mike A., Raitakari, Olli T., Ichihara, Sahoko, Wild, Sarah H., Nelson, Christopher P., Campbell, Harry, Jäger, Susanne, Nabika, Toru, Al-Mulla, Fahd, Niinikoski, Harri, Braund, Peter S., Kolcic, Ivana, Kovacs, Peter, Giardoglou, Tota, Katsuya, Tomohiro, Bhatti, Konain Fatima, de Kleijn, Dominique, de Borst, Gert J., Kim, Eung Kweon, Adams, Hieab H. H., Ikram, M. Arfan, Zhu, Xiaofeng, Asselbergs, Folkert W., Kraaijeveld, Adriaan O., Beulens, Joline W. J., Shu, Xiao-Ou, Rallidis, Loukianos S., Pedersen, Oluf, Hansen, Torben, Mitchell, Paul, Hewitt, Alex W., Kähönen, Mika, Pérusse, Louis, Bouchard, Claude, Tönjes, Anke, Chen, Yii-Der Ida, Pennell, Craig E., Mori, Trevor A., Lieb, Wolfgang, Franke, Andre, Ohlsson, Claes, Mellström, Dan, Cho, Yoon Shin, Lee, Hyejin, Yuan, Jian-Min, Koh, Woon-Puay, Rhee, Sang Youl, Woo, Jeong-Taek, Heid, Iris M., Stark, Klaus J., Völzke, Henry, Homuth, Georg, Evans, Michele K., Zonderman, Alan B., Polasek, Ozren, Pasterkamp, Gerard, Hoefer, Imo E., Redline, Susan, Pahkala, Katja, Oldehinkel, Albertine J., Snieder, Harold, Biino, Ginevra, Schmidt, Reinhold, Schmidt, Helena, Chen, Y. Eugene, Bandinelli, Stefania, Dedoussis, George, Thanaraj, Thangavel Alphonse, Kardia, Sharon L. R., Kato, Norihiro, Schulze, Matthias B., Girotto, Giorgia, Jung, Bettina, Böger, Carsten A., Joshi, Peter K., Bennett, David A., De Jager, Philip L., Lu, Xiangfeng, Mamakou, Vasiliki, Brown, Morris, Caulfield, Mark J., Munroe, Patricia B., Guo, Xiuqing, Ciullo, Marina, Jonas, Jost B., Samani, Nilesh J., Kaprio, Jaakko, Pajukanta, Päivi, Adair, Linda S., Bechayda, Sonny Augustin, de Silva, H. Janaka, Wickremasinghe, Ananda R., Krauss, Ronald M., Wu, Jer-Yuarn, Zheng, Wei, den Hollander, Anneke I., Bharadwaj, Dwaipayan, Correa, Adolfo, Wilson, James G., Lind, Lars, Heng, Chew-Kiat, Nelson, Amanda E., Golightly, Yvonne M., Wilson, James F., Penninx, Brenda, Kim, Hyung-Lae, Attia, John, Scott, Rodney J., Rao, D. C., Arnett, Donna K., Hunt, Steven C., Walker, Mark, Koistinen, Heikki A., Chandak, Giriraj R., Yajnik, Chittaranjan S., Mercader, Josep M., Tusié-Luna, Teresa, Aguilar-Salinas, Carlos A., Villalpando, Clicerio Gonzalez, Orozco, Lorena, Fornage, Myriam, Tai, E. Shyong, van Dam, Rob M., Lehtimäki, Terho, Chaturvedi, Nish, Yokota, Mitsuhiro, Liu, Jianjun, Reilly, Dermot F., McKnight, Amy Jayne, Kee, Frank, Jöckel, Karl-Heinz, McCarthy, Mark I., Palmer, Colin N. A., Vitart, Veronique, Hayward, Caroline, Simonsick, Eleanor, van Duijn, Cornelia M., Lu, Fan, Qu, Jia, Hishigaki, Haretsugu, Lin, Xu, März, Winfried, Parra, Esteban J., Cruz, Miguel, Gudnason, Vilmundur, Tardif, Jean-Claude, Lettre, Guillaume, ’t Hart, Leen M., Elders, Petra J. M., Damrauer, Scott M., Kumari, Meena, Kivimaki, Mika, van der Harst, Pim, Spector, Tim D., Loos, Ruth J. F., Province, Michael A., Psaty, Bruce M., Brandslund, Ivan, Pramstaller, Peter P., Christensen, Kaare, Ripatti, Samuli, Widén, Elisabeth, Hakonarson, Hakon, Grant, Struan F. A., Kiemeney, Lambertus A. L. M., de Graaf, Jacqueline, Loeffler, Markus, Kronenberg, Florian, Gu, Dongfeng, Erdmann, Jeanette, Schunkert, Heribert, Franks, Paul W., Linneberg, Allan, Jukema, J. Wouter, Khera, Amit V., Männikkö, Minna, Jarvelin, Marjo-Riitta, Kutalik, Zoltan, Cucca, Francesco, Mook-Kanamori, Dennis O., van Dijk, Ko Willems, Watkins, Hugh, Strachan, David P., Grarup, Niels, Sever, Peter, Poulter, Neil, Rotter, Jerome I., Dantoft, Thomas M., Karpe, Fredrik, Neville, Matt J., Timpson, Nicholas J., Cheng, Ching-Yu, Wong, Tien-Yin, Khor, Chiea Chuen, Sabanayagam, Charumathi, Peters, Annette, Gieger, Christian, Hattersley, Andrew T., Pedersen, Nancy L., Magnusson, Patrik K. E., Boomsma, Dorret I., de Geus, Eco J. C., Cupples, L. Adrienne, van Meurs, Joyce B. J., Ghanbari, Mohsen, Gordon-Larsen, Penny, Huang, Wei, Kim, Young Jin, Tabara, Yasuharu, Wareham, Nicholas J., Langenberg, Claudia, Zeggini, Eleftheria, Kuusisto, Johanna, Laakso, Markku, Ingelsson, Erik, Abecasis, Goncalo, Chambers, John C., Kooner, Jaspal S., de Vries, Paul S., Morrison, Alanna C., North, Kari E., Daviglus, Martha, Kraft, Peter, Martin, Nicholas G., Whitfield, John B., Abbas, Shahid, Saleheen, Danish, Walters, Robin G., Holmes, Michael V., Black, Corri, Smith, Blair H., Justice, Anne E., Baras, Aris, Buring, Julie E., Ridker, Paul M., Chasman, Daniel I., Kooperberg, Charles, Wei, Wei-Qi, Jarvik, Gail P., Namjou, Bahram, Hayes, M. Geoffrey, Ritchie, Marylyn D., Jousilahti, Pekka, Salomaa, Veikko, Hveem, Kristian, Åsvold, Bjørn Olav, Kubo, Michiaki, Kamatani, Yoichiro, Okada, Yukinori, Murakami, Yoshinori, Thorsteinsdottir, Unnur, Stefansson, Kari, Ho, Yuk-Lam, Lynch, Julie A., Rader, Daniel J., Tsao, Philip S., Chang, Kyong-Mi, Cho, Kelly, O’Donnell, Christopher J., Gaziano, John M., Wilson, Peter, Rotimi, Charles N., Hazelhurst, Scott, Ramsay, Michèle, Trembath, Richard C., van Heel, David A., Tamiya, Gen, Yamamoto, Masayuki, Kim, Bong-Jo, Mohlke, Karen L., Frayling, Timothy M., Hirschhorn, Joel N., Kathiresan, Sekar, Boehnke, Michael, Natarajan, Pradeep, Peloso, Gina M., Brown, Christopher D., Morris, Andrew P., Assimes, Themistocles L., Deloukas, Panos, Sun, Yan V., and Willer, Cristen J.
Abstract: Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4–23have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26application of polygenic scores in clinical practice.
Published: 2021
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11. 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, A. R. V. R., 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, Kavousi, Maryam, Khor, Chiea Chuen, Kilpeläinen, Tuomas O., Koh, Woon-Puay, Komulainen, Pirjo, Kraja, Aldi T., Krieger, J. E., Langefeld, Carl D., Li, Yize, Liang, Jingjing, Liewald, David C. M., Liu, Ching-Ti, Liu, Jianjun, Lohman, Kurt K., Mägi, Reedik, McKenzie, Colin A., Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, Milani, Lili, Mook-Kanamori, Dennis O., Nalls, Mike A., Nelson, Christopher P., Norris, Jill M., O’Connell, Jeff, Ogunniyi, Adesola, Padmanabhan, Sandosh, Palmer, Nicholette D., Pedersen, Nancy L., Perls, Thomas, Peters, Annette, Petersmann, Astrid, Peyser, Patricia A., Polasek, Ozren, Porteous, David J., Raffel, Leslie J., Rice, Treva K., Rotter, Jerome I., Rudan, Igor, Rueda-Ochoa, Oscar-Leonel, Sabanayagam, Charumathi, Salako, Babatunde L., Schreiner, Pamela J., Shikany, James M., Sidney, Stephen S., Sims, Mario, Sitlani, Colleen M., Smith, Jennifer A., Starr, John M., Strauch, Konstantin, Swertz, Morris A., Teumer, Alexander, Tham, Yih Chung, Uitterlinden, André G., Vaidya, Dhananjay, van der Ende, M. Yldau, Waldenberger, Melanie, Wang, Lihua, Wang, Ya-Xing, Wei, Wen-Bin, Weir, David R., Wen, Wanqing, Yao, Jie, Yu, Bing, Yu, Caizheng, Yuan, Jian-Min, Zhao, Wei, Zonderman, Alan B., Becker, Diane M., Bowden, Donald W., Deary, Ian J., Dörr, Marcus, Esko, Tõnu, Freedman, Barry I., Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Jonas, Jost Bruno, Kammerer, Candace M., Kato, Norihiro, Lakka, Timo A., Leander, Karin, Lehtimäki, Terho, Magnusson, Patrik K. E., Marques-Vidal, Pedro, Penninx, Brenda W. J. H., Samani, Nilesh J., van der Harst, Pim, Wagenknecht, Lynne E., Wu, Tangchun, Zheng, Wei, Zhu, Xiaofeng, Bouchard, Claude, Cooper, Richard S., Correa, Adolfo, Evans, Michele K., Gudnason, Vilmundur, Hayward, Caroline, Horta, Bernardo L., Kelly, Tanika N., Kritchevsky, Stephen B., Levy, Daniel, Palmas, Walter R., Pereira, A. C., Province, Michael M., Psaty, Bruce M., Ridker, Paul M., Rotimi, Charles N., Tai, E. Shyong, van Dam, Rob M., van Duijn, Cornelia M., Wong, Tien Yin, Rice, Kenneth, Gauderman, W. James, Morrison, Alanna C., North, Kari E., Kardia, Sharon L. R., Caulfield, Mark J., Elliott, Paul, Munroe, Patricia B., Franks, Paul W., Rao, Dabeeru C., and Fornage, Myriam
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< 5 × 10-8). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
Published: 2021
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12. 9p21.3 Coronary Artery Disease Locus Identifies Patients With Treatment Benefit From Bariatric Surgery in the Nonrandomized Prospective Controlled Swedish Obese Subjects Study

Author: Jacobson, Peter, Peltonen, Markku, Svensson, Per-Arne, Taube, Magdalena, Andersson-Assarsson, Johanna C., Sjoholm, Kajsa, Bouchard, Claude, Carlsson, Björn, and Carlsson, Lena M.S.
Abstract: Supplemental Digital Content is available in the text.
Published: 2020
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13. Polygenic Risk, Fitness, and Obesity in the Coronary Artery Risk Development in Young Adults (CARDIA) Study

Author: Murthy, Venkatesh L., Xia, Rui, Baldridge, Abigail S., Carnethon, Mercedes R., Sidney, Stephen, Bouchard, Claude, Sarzynski, Mark A., Lima, João A. C., Lewis, Gregory D., Shah, Sanjiv J., Fornage, Myriam, and Shah, Ravi V.
Abstract: IMPORTANCE: Obesity is a major determinant of disease burden worldwide. Polygenic risk scores (PRSs) have been posited as key predictors of obesity. How a PRS can be translated to the clinical encounter (especially in the context of fitness, activity, and parental history of overweight) remains unclear. OBJECTIVE: To quantify the relative importance of a PRS, fitness, activity, parental history of overweight, and body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) in young adulthood on BMI trends over 25 years. DESIGN, SETTING, AND PARTICIPANTS: This population-based prospective cohort study at 4 US centers included white individuals and black individuals with assessments of polygenic risk of obesity, fitness, activity, and BMI in young adulthood (in their 20s) and up to 25 years of follow-up. Data collected between March 1985 and August 2011 were analyzed from April 25, 2019, to September 29, 2019. MAIN OUTCOMES AND MEASURES: Body mass index at the initial visit and 25 years later. RESULTS: This study evaluated an obesity PRS from a recently reported study of 1608 white individuals (848 women [52.7%]) and 909 black individuals (548 women [60.3%]) across the United States. At baseline (year 0), mean (SD) overall BMI was 24.2 (4.5), which increased to 29.6 (6.9) at year 25. Among white individuals, the PRS (combined with age, sex, self-reported parental history of overweight, and principal components of ancestry) explained 11.9% (at year 0) and 13.6% (at year 25) of variation in BMI. Although the addition of fitness increased the explanatory capability of the model (24.0% variance at baseline and up to 18.1% variance in BMI at year 25), baseline BMI in young adulthood was the strongest factor, explaining 52.3% of BMI in midlife in combination with age, sex, and self-reported parental history of overweight. Accordingly, models that included baseline BMI (especially BMI surveillance over time) were better in predicting BMI at year 25 compared with the PRS. In fully adjusted models, the effect sizes for fitness and the PRS on BMI were comparable in opposing directions. The added explanatory capacity of the PRS among black individuals was lower than among white individuals. Among white individuals, addition of baseline BMI and surveillance of BMI over time was associated with improved precision of predicted BMI at year 25 (mean error in predicted BMI 0 kg/m2 [95% CI, −11.4 to 11.4] to 0 kg/m2 [95% CI, −8.5 to 8.5] for baseline BMI and mean error 0 kg/m2 [95% CI, −5.3 to 5.3] for BMI surveillance). CONCLUSIONS AND RELEVANCE: Cardiorespiratory fitness in young adulthood and a PRS are modestly associated with midlife BMI, although future BMI is associated with BMI in young adulthood. Fitness has a comparable association with future BMI as does the PRS. Caution should be exercised in the widespread use of polygenic risk for obesity prevention in adults, and close clinical surveillance and fitness may have prime roles in limiting the adverse consequences of elevated BMI on health.
Published: 2020
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14. Plasma protein patterns as comprehensive indicators of health

Author: Williams, Stephen A., Kivimaki, Mika, Langenberg, Claudia, Hingorani, Aroon D., Casas, J. P., Bouchard, Claude, Jonasson, Christian, Sarzynski, Mark A., Shipley, Martin J., Alexander, Leigh, Ash, Jessica, Bauer, Tim, Chadwick, Jessica, Datta, Gargi, DeLisle, Robert Kirk, Hagar, Yolanda, Hinterberg, Michael, Ostroff, Rachel, Weiss, Sophie, Ganz, Peter, and Wareham, Nicholas J.
Abstract: Proteins are effector molecules that mediate the functions of genes1,2and modulate comorbidities3–10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12–16coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check.
Published: 2019
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15. 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 J. A., 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, D. C., Qi, Qibin, Ferrucci, Luigi, Ericson, Ulrika, Blangero, John, Hofman, Albert, Pausova, Zdenka, Mikkilä, Vera, Wareham, Nick J., Kardia, Sharon L. R, 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 I. A., 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., Paus, Tomas, Florez, Jose C., Deloukas, Panos, Lyytikäinen, Leo-Pekka, Chasman, Daniel I., Chu, Audrey Y., and Tanaka, Toshiko
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< 1 × 10−6) associated with intake of any macronutrient in 91,114 European ancestry participants. Four loci replicated and reached genome-wide significance in a combined meta-analysis including 123,659 European descent participants, unraveling two novel loci; a common variant in RARBlocus for carbohydrate intake and a rare variant in DRAM1locus for protein intake, and corroborating earlier FGF21and FTOfindings. In additional analysis of 144,770 participants from the UK Biobank, all identified associations from the two-stage analysis were confirmed except for DRAM1. Identified loci might have implications in brain and adipose tissue biology and have clinical impact in obesity-related phenotypes. Our findings provide new insight into biological functions related to macronutrient intake.
Published: 2019
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16. Author Correction: The power of genetic diversity in genome-wide association studies of lipids

Author: Graham, Sarah E., Clarke, Shoa L., Wu, Kuan-Han H., Kanoni, Stavroula, Zajac, Greg J. M., Ramdas, Shweta, Surakka, Ida, Ntalla, Ioanna, Vedantam, Sailaja, Winkler, Thomas W., Locke, Adam E., Marouli, Eirini, Hwang, Mi Yeong, Han, Sohee, Narita, Akira, Choudhury, Ananyo, Bentley, Amy R., Ekoru, Kenneth, Verma, Anurag, Trivedi, Bhavi, Martin, Hilary C., Hunt, Karen A., Hui, Qin, Klarin, Derek, Zhu, Xiang, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F., Holm, Hilma, Olafsson, Isleifur, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M., Rasheed, Humaira, Ruotsalainen, Sanni E., Havulinna, Aki S., Veturi, Yogasudha, Feng, QiPing, Rosenthal, Elisabeth A., Lingren, Todd, Pacheco, Jennifer Allen, Pendergrass, Sarah A., Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E., Campbell, Archie, Lin, Kuang, Millwood, Iona Y., Hindy, George, Rasheed, Asif, Faul, Jessica D., Zhao, Wei, Weir, David R., Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Mahajan, Anubha, Brown, Michael R., Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M., Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian’an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Willemsen, Gonneke, Wood, Andrew R., Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E., Chai, Jin Fang, Aadahl, Mette, Yao, Jie, Manichaikul, Ani, Warren, Helen R., Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L., Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Sidore, Carlo, Fiorillo, Edoardo, McDaid, Aaron F., Marques-Vidal, Pedro, Wielscher, Matthias, Trompet, Stella, Sattar, Naveed, Møllehave, Line T., Thuesen, Betina H., Munz, Matthias, Zeng, Lingyao, Huang, Jianfeng, Yang, Bin, Poveda, Alaitz, Kurbasic, Azra, Lamina, Claudia, Forer, Lukas, Scholz, Markus, Galesloot, Tessel E., Bradfield, Jonathan P., Daw, E. Warwick, Zmuda, Joseph M., Mitchell, Jonathan S., Fuchsberger, Christian, Christensen, Henry, Brody, Jennifer A., Feitosa, Mary F., Wojczynski, Mary K., Preuss, Michael, Mangino, Massimo, Christofidou, Paraskevi, Verweij, Niek, Benjamins, Jan W., Engmann, Jorgen, Kember, Rachel L., Slieker, Roderick C., Lo, Ken Sin, Zilhao, Nuno R., Le, Phuong, Kleber, Marcus E., Delgado, Graciela E., Huo, Shaofeng, Ikeda, Daisuke D., Iha, Hiroyuki, Yang, Jian, Liu, Jun, Leonard, Hampton L., Marten, Jonathan, Schmidt, Börge, Arendt, Marina, Smyth, Laura J., Cañadas-Garre, Marisa, Wang, Chaolong, Nakatochi, Masahiro, Wong, Andrew, Hutri-Kähönen, Nina, Sim, Xueling, Xia, Rui, Huerta-Chagoya, Alicia, Fernandez-Lopez, Juan Carlos, Lyssenko, Valeriya, Ahmed, Meraj, Jackson, Anne U., Yousri, Noha A., Irvin, Marguerite R., Oldmeadow, Christopher, Kim, Han-Na, Ryu, Seungho, Timmers, Paul R. H. J., Arbeeva, Liubov, Dorajoo, Rajkumar, Lange, Leslie A., Chai, Xiaoran, Prasad, Gauri, Lorés-Motta, Laura, Pauper, Marc, Long, Jirong, Li, Xiaohui, Theusch, Elizabeth, Takeuchi, Fumihiko, Spracklen, Cassandra N., Loukola, Anu, Bollepalli, Sailalitha, Warner, Sophie C., Wang, Ya Xing, Wei, Wen B., Nutile, Teresa, Ruggiero, Daniela, Sung, Yun Ju, Hung, Yi-Jen, Chen, Shufeng, Liu, Fangchao, Yang, Jingyun, Kentistou, Katherine A., Gorski, Mathias, Brumat, Marco, Meidtner, Karina, Bielak, Lawrence F., Smith, Jennifer A., Hebbar, Prashantha, Farmaki, Aliki-Eleni, Hofer, Edith, Lin, Maoxuan, Xue, Chao, Zhang, Jifeng, Concas, Maria Pina, Vaccargiu, Simona, van der Most, Peter J., Pitkänen, Niina, Cade, Brian E., Lee, Jiwon, van der Laan, Sander W., Chitrala, Kumaraswamy Naidu, Weiss, Stefan, Zimmermann, Martina E., Lee, Jong Young, Choi, Hyeok Sun, Nethander, Maria, Freitag-Wolf, Sandra, Southam, Lorraine, Rayner, Nigel W., Wang, Carol A., Lin, Shih-Yi, Wang, Jun-Sing, Couture, Christian, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Cuellar-Partida, Gabriel, Vestergaard, Henrik, Hildalgo, Bertha, Giannakopoulou, Olga, Cai, Qiuyin, Obura, Morgan O., van Setten, Jessica, Li, Xiaoyin, Schwander, Karen, Terzikhan, Natalie, Shin, Jae Hun, Jackson, Rebecca D., Reiner, Alexander P., Martin, Lisa Warsinger, Chen, Zhengming, Li, Liming, Highland, Heather M., Young, Kristin L., Kawaguchi, Takahisa, Thiery, Joachim, Bis, Joshua C., Nadkarni, Girish N., Launer, Lenore J., Li, Huaixing, Nalls, Mike A., Raitakari, Olli T., Ichihara, Sahoko, Wild, Sarah H., Nelson, Christopher P., Campbell, Harry, Jäger, Susanne, Nabika, Toru, Al-Mulla, Fahd, Niinikoski, Harri, Braund, Peter S., Kolcic, Ivana, Kovacs, Peter, Giardoglou, Tota, Katsuya, Tomohiro, Bhatti, Konain Fatima, de Kleijn, Dominique, de Borst, Gert J., Kim, Eung Kweon, Adams, Hieab H. H., Ikram, M. Arfan, Zhu, Xiaofeng, Asselbergs, Folkert W., Kraaijeveld, Adriaan O., Beulens, Joline W. J., Shu, Xiao-Ou, Rallidis, Loukianos S., Pedersen, Oluf, Hansen, Torben, Mitchell, Paul, Hewitt, Alex W., Kähönen, Mika, Pérusse, Louis, Bouchard, Claude, Tönjes, Anke, Chen, Yii-Der Ida, Pennell, Craig E., Mori, Trevor A., Lieb, Wolfgang, Franke, Andre, Ohlsson, Claes, Mellström, Dan, Cho, Yoon Shin, Lee, Hyejin, Yuan, Jian-Min, Koh, Woon-Puay, Rhee, Sang Youl, Woo, Jeong-Taek, Heid, Iris M., Stark, Klaus J., Völzke, Henry, Homuth, Georg, Evans, Michele K., Zonderman, Alan B., Polasek, Ozren, Pasterkamp, Gerard, Hoefer, Imo E., Redline, Susan, Pahkala, Katja, Oldehinkel, Albertine J., Snieder, Harold, Biino, Ginevra, Schmidt, Reinhold, Schmidt, Helena, Chen, Y. Eugene, Bandinelli, Stefania, Dedoussis, George, Thanaraj, Thangavel Alphonse, Kardia, Sharon L. R., Kato, Norihiro, Schulze, Matthias B., Girotto, Giorgia, Jung, Bettina, Böger, Carsten A., Joshi, Peter K., Bennett, David A., De Jager, Philip L., Lu, Xiangfeng, Mamakou, Vasiliki, Brown, Morris, Caulfield, Mark J., Munroe, Patricia B., Guo, Xiuqing, Ciullo, Marina, Jonas, Jost B., Samani, Nilesh J., Kaprio, Jaakko, Pajukanta, Päivi, Adair, Linda S., Bechayda, Sonny Augustin, de Silva, H. Janaka, Wickremasinghe, Ananda R., Krauss, Ronald M., Wu, Jer-Yuarn, Zheng, Wei, den Hollander, Anneke I., Bharadwaj, Dwaipayan, Correa, Adolfo, Wilson, James G., Lind, Lars, Heng, Chew-Kiat, Nelson, Amanda E., Golightly, Yvonne M., Wilson, James F., Penninx, Brenda, Kim, Hyung-Lae, Attia, John, Scott, Rodney J., Rao, D. C., Arnett, Donna K., Hunt, Steven C., Walker, Mark, Koistinen, Heikki A., Chandak, Giriraj R., Yajnik, Chittaranjan S., Mercader, Josep M., Tusié-Luna, Teresa, Aguilar-Salinas, Carlos A., Villalpando, Clicerio Gonzalez, Orozco, Lorena, Fornage, Myriam, Tai, E. Shyong, van Dam, Rob M., Lehtimäki, Terho, Chaturvedi, Nish, Yokota, Mitsuhiro, Liu, Jianjun, Reilly, Dermot F., McKnight, Amy Jayne, Kee, Frank, Jöckel, Karl-Heinz, McCarthy, Mark I., Palmer, Colin N. A., Vitart, Veronique, Hayward, Caroline, Simonsick, Eleanor, van Duijn, Cornelia M., Lu, Fan, Qu, Jia, Hishigaki, Haretsugu, Lin, Xu, März, Winfried, Parra, Esteban J., Cruz, Miguel, Gudnason, Vilmundur, Tardif, Jean-Claude, Lettre, Guillaume, ’t Hart, Leen M., Elders, Petra J. M., Damrauer, Scott M., Kumari, Meena, Kivimaki, Mika, van der Harst, Pim, Spector, Tim D., Loos, Ruth J. F., Province, Michael A., Psaty, Bruce M., Brandslund, Ivan, Pramstaller, Peter P., Christensen, Kaare, Ripatti, Samuli, Widén, Elisabeth, Hakonarson, Hakon, Grant, Struan F. A., Kiemeney, Lambertus A. L. M., de Graaf, Jacqueline, Loeffler, Markus, Kronenberg, Florian, Gu, Dongfeng, Erdmann, Jeanette, Schunkert, Heribert, Franks, Paul W., Linneberg, Allan, Jukema, J. Wouter, Khera, Amit V., Männikkö, Minna, Jarvelin, Marjo-Riitta, Kutalik, Zoltan, Cucca, Francesco, Mook-Kanamori, Dennis O., van Dijk, Ko Willems, Watkins, Hugh, Strachan, David P., Grarup, Niels, Sever, Peter, Poulter, Neil, Rotter, Jerome I., Dantoft, Thomas M., Karpe, Fredrik, Neville, Matt J., Timpson, Nicholas J., Cheng, Ching-Yu, Wong, Tien-Yin, Khor, Chiea Chuen, Sabanayagam, Charumathi, Peters, Annette, Gieger, Christian, Hattersley, Andrew T., Pedersen, Nancy L., Magnusson, Patrik K. E., Boomsma, Dorret I., de Geus, Eco J. C., Cupples, L. Adrienne, van Meurs, Joyce B. J., Ghanbari, Mohsen, Gordon-Larsen, Penny, Huang, Wei, Kim, Young Jin, Tabara, Yasuharu, Wareham, Nicholas J., Langenberg, Claudia, Zeggini, Eleftheria, Kuusisto, Johanna, Laakso, Markku, Ingelsson, Erik, Abecasis, Goncalo, Chambers, John C., Kooner, Jaspal S., de Vries, Paul S., Morrison, Alanna C., North, Kari E., Daviglus, Martha, Kraft, Peter, Martin, Nicholas G., Whitfield, John B., Abbas, Shahid, Saleheen, Danish, Walters, Robin G., Holmes, Michael V., Black, Corri, Smith, Blair H., Justice, Anne E., Baras, Aris, Buring, Julie E., Ridker, Paul M., Chasman, Daniel I., Kooperberg, Charles, Wei, Wei-Qi, Jarvik, Gail P., Namjou, Bahram, Hayes, M. Geoffrey, Ritchie, Marylyn D., Jousilahti, Pekka, Salomaa, Veikko, Hveem, Kristian, Åsvold, Bjørn Olav, Kubo, Michiaki, Kamatani, Yoichiro, Okada, Yukinori, Murakami, Yoshinori, Thorsteinsdottir, Unnur, Stefansson, Kari, Ho, Yuk-Lam, Lynch, Julie A., Rader, Daniel J., Tsao, Philip S., Chang, Kyong-Mi, Cho, Kelly, O’Donnell, Christopher J., Gaziano, John M., Wilson, Peter, Rotimi, Charles N., Hazelhurst, Scott, Ramsay, Michèle, Trembath, Richard C., van Heel, David A., Tamiya, Gen, Yamamoto, Masayuki, Kim, Bong-Jo, Mohlke, Karen L., Frayling, Timothy M., Hirschhorn, Joel N., Kathiresan, Sekar, Boehnke, Michael, Natarajan, Pradeep, Peloso, Gina M., Brown, Christopher D., Morris, Andrew P., Assimes, Themistocles L., Deloukas, Panos, Sun, Yan V., and Willer, Cristen J.
Published: 2023
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17. 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, D.C., 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., and Sethupathy, Praveen
Abstract: Objective Identify determinants of plasma adropin concentrations, a secreted peptide translated from the Energy Homeostasis Associated ( ENHO ) gene linked to metabolic control and vascular function. Methods Associations 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. Results In 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. Conclusions In 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. [ABSTRACT FROM AUTHOR]
Published: 2018
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18. Association of Dimethylguanidino Valeric Acid With Partial Resistance to Metabolic Health Benefits of Regular Exercise

Author: Robbins, Jeremy M., Herzig, Matthew, Morningstar, Jordan, Sarzynski, Mark A., Cruz, Daniel E., Wang, Thomas J., Gao, Yan, Wilson, James G., Bouchard, Claude, Rankinen, Tuomo, and Gerszten, Robert E.
Abstract: IMPORTANCE: Metabolic responses to exercise training are variable. Metabolite profiling may aid in the clinical assessment of an individual’s responsiveness to exercise interventions. OBJECTIVE: To investigate the association between a novel circulating biomarker of hepatic fat, dimethylguanidino valeric acid (DMGV), and metabolic health traits before and after 20 weeks of endurance exercise training. DESIGN, SETTING, AND PARTICIPANTS: This study involved cross-sectional and longitudinal analyses of the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study, a 20-week, single-arm endurance exercise clinical trial performed in multiple centers between 1993 and 1997. White participants with sedentary lifestyles who were free of cardiometabolic disease were included. Metabolomic tests were performed using a liquid chromatography, tandem mass spectrometry method on plasma samples collected before and after exercise training in the HERITAGE study. Metabolomics and data analysis were performed from August 2017 to May 2018. EXPOSURES: Plasma DMGV levels. MAIN OUTCOME AND MEASURES: The association between DMGV levels and measures of body composition, plasma lipids, insulin, and glucose homeostasis before and after exercise training. RESULTS: Among the 439 participants included in analyses from HERITAGE, the mean (SD) age was 36 (15) years, 228 (51.9%) were female, and the median (interquartile range) body mass index was 25 (22-28). Baseline levels of DMGV were positively associated with body fat percentage, abdominal visceral fat, very low-density lipoprotein cholesterol, and triglycerides, and inversely associated with insulin sensitivity, low-density lipoprotein cholesterol, high-density lipoprotein size, and high-density lipoprotein cholesterol (range of β coefficients, 0.17-0.46 [SEs, 0.026-0.050]; all P < .001, after adjusting for age and sex). After adjusting for age, sex, and baseline traits, baseline DMGV levels were positively associated with changes in small high-density lipoprotein particles (β, 0.14 [95% CI, 0.05-0.23]) and inversely associated with changes in medium and total high-density lipoprotein particles (β, −0.15 [95% CI, −0.24 to −0.05] and −0.19 [95% CI, −0.28 to −0.10], respectively), apolipoprotein A1 (β, −0.14 [95% CI, −0.23 to −0.05]), and insulin sensitivity (β, −0.13; P = 3.0 × 10−3) after exercise training. CONCLUSIONS AND RELEVANCE: Dimethylguanidino valeric acid is an early marker of cardiometabolic dysfunction that is associated with attenuated improvements in lipid traits and insulin sensitivity after exercise training. Levels of DMGV may identify individuals who require additional therapies beyond guideline-directed exercise to improve their metabolic health.
Published: 2019
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19. Multi-ancestry genome-wide gene–smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids

Author: Bentley, Amy R., Sung, Yun J., Brown, Michael R., Winkler, Thomas W., Kraja, Aldi T., Ntalla, Ioanna, Schwander, Karen, Chasman, Daniel I., Lim, Elise, Deng, Xuan, Guo, Xiuqing, Liu, Jingmin, Lu, Yingchang, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Huffman, Jennifer E., Musani, Solomon K., Li, Changwei, Feitosa, Mary F., Richard, Melissa A., Noordam, Raymond, Baker, Jenna, Chen, Guanjie, Aschard, Hugues, Bartz, Traci M., Ding, Jingzhong, Dorajoo, Rajkumar, Manning, Alisa K., Rankinen, Tuomo, Smith, Albert V., Tajuddin, Salman M., Zhao, Wei, Graff, Mariaelisa, Alver, Maris, Boissel, Mathilde, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Evangelou, Evangelos, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E., Hartwig, Fernando P., He, Meian, Horimoto, Andrea R. V. R., Hsu, Fang-Chi, Hung, Yi-Jen, Jackson, Anne U., Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Leander, Karin, Lin, Keng-Hung, Luan, Jian’an, Lyytikäinen, Leo-Pekka, Matoba, Nana, Nolte, Ilja M., Pietzner, Maik, Prins, Bram, Riaz, Muhammad, Robino, Antonietta, Said, M. Abdullah, Schupf, Nicole, Scott, Robert A., Sofer, Tamar, Stancáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O., van der Most, Peter J., Varga, Tibor V., Wang, Tzung-Dau, Wang, Yajuan, Ware, Erin B., Wen, Wanqing, Xiang, Yong-Bing, Yanek, Lisa R., Zhang, Weihua, Zhao, Jing Hua, Adeyemo, Adebowale, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E., Arzumanyan, Zorayr, Aung, Tin, Ballantyne, Christie, Barr, R. Graham, Bielak, Lawrence F., Boerwinkle, Eric, Bottinger, Erwin P., Broeckel, Ulrich, Brown, Morris, Cade, Brian E., Campbell, Archie, Canouil, Mickaël, Charumathi, Sabanayagam, Chen, Yii-Der Ida, Christensen, Kaare, Concas, Maria Pina, Connell, John M., de las Fuentes, Lisa, de Silva, H. Janaka, de Vries, Paul S., Doumatey, Ayo, Duan, Qing, Eaton, Charles B., Eppinga, Ruben N., Faul, Jessica D., Floyd, James S., Forouhi, Nita G., Forrester, Terrence, Friedlander, Yechiel, Gandin, Ilaria, Gao, He, Ghanbari, Mohsen, Gharib, Sina A., Gigante, Bruna, Giulianini, Franco, Grabe, Hans J., Gu, C. Charles, Harris, Tamara B., Heikkinen, Sami, Heng, Chew-Kiat, Hirata, Makoto, Hixson, James E., Ikram, M. Arfan, Jia, Yucheng, Joehanes, Roby, Johnson, Craig, Jonas, Jost Bruno, Justice, Anne E., Katsuya, Tomohiro, Khor, Chiea Chuen, Kilpeläinen, Tuomas O., Koh, Woon-Puay, Kolcic, Ivana, Kooperberg, Charles, Krieger, Jose E., Kritchevsky, Stephen B., Kubo, Michiaki, Kuusisto, Johanna, Lakka, Timo A., Langefeld, Carl D., Langenberg, Claudia, Launer, Lenore J., Lehne, Benjamin, Lewis, Cora E., Li, Yize, Liang, Jingjing, Lin, Shiow, Liu, Ching-Ti, Liu, Jianjun, Liu, Kiang, Loh, Marie, Lohman, Kurt K., Louie, Tin, Luzzi, Anna, Mägi, Reedik, Mahajan, Anubha, Manichaikul, Ani W., McKenzie, Colin A., Meitinger, Thomas, Metspalu, Andres, Milaneschi, Yuri, Milani, Lili, Mohlke, Karen L., Momozawa, Yukihide, Morris, Andrew P., Murray, Alison D., Nalls, Mike A., Nauck, Matthias, Nelson, Christopher P., North, Kari E., O’Connell, Jeffrey R., Palmer, Nicholette D., Papanicolau, George J., Pedersen, Nancy L., Peters, Annette, Peyser, Patricia A., Polasek, Ozren, Poulter, Neil, Raitakari, Olli T., Reiner, Alex P., Renström, Frida, Rice, Treva K., Rich, Stephen S., Robinson, Jennifer G., Rose, Lynda M., Rosendaal, Frits R., Rudan, Igor, Schmidt, Carsten O., Schreiner, Pamela J., Scott, William R., Sever, Peter, Shi, Yuan, Sidney, Stephen, Sims, Mario, Smith, Jennifer A., Snieder, Harold, Starr, John M., Strauch, Konstantin, Stringham, Heather M., Tan, Nicholas Y. Q., Tang, Hua, Taylor, Kent D., Teo, Yik Ying, Tham, Yih Chung, Tiemeier, Henning, Turner, Stephen T., Uitterlinden, André G., van Heemst, Diana, Waldenberger, Melanie, Wang, Heming, Wang, Lan, Wang, Lihua, Wei, Wen Bin, Williams, Christine A., Wilson, Gregory, Wojczynski, Mary K., Yao, Jie, Young, Kristin, Yu, Caizheng, Yuan, Jian-Min, Zhou, Jie, Zonderman, Alan B., Becker, Diane M., Boehnke, Michael, Bowden, Donald W., Chambers, John C., Cooper, Richard S., de Faire, Ulf, Deary, Ian J., Elliott, Paul, Esko, Tõnu, Farrall, Martin, Franks, Paul W., Freedman, Barry I., Froguel, Philippe, Gasparini, Paolo, Gieger, Christian, Horta, Bernardo L., Juang, Jyh-Ming Jimmy, Kamatani, Yoichiro, Kammerer, Candace M., Kato, Norihiro, Kooner, Jaspal S., Laakso, Markku, Laurie, Cathy C., Lee, I-Te, Lehtimäki, Terho, Magnusson, Patrik K. E., Oldehinkel, Albertine J., Penninx, Brenda W. J. H., Pereira, Alexandre C., Rauramaa, Rainer, Redline, Susan, Samani, Nilesh J., Scott, James, Shu, Xiao-Ou, van der Harst, Pim, Wagenknecht, Lynne E., Wang, Jun-Sing, Wang, Ya Xing, Wareham, Nicholas J., Watkins, Hugh, Weir, David R., Wickremasinghe, Ananda R., Wu, Tangchun, Zeggini, Eleftheria, Zheng, Wei, Bouchard, Claude, Evans, Michele K., Gudnason, Vilmundur, Kardia, Sharon L. R., Liu, Yongmei, Psaty, Bruce M., Ridker, Paul M., van Dam, Rob M., Mook-Kanamori, Dennis O., Fornage, Myriam, Province, Michael A., Kelly, Tanika N., Fox, Ervin R., Hayward, Caroline, van Duijn, Cornelia M., Tai, E. Shyong, Wong, Tien Yin, Loos, Ruth J. F., Franceschini, Nora, Rotter, Jerome I., Zhu, Xiaofeng, Bierut, Laura J., Gauderman, W. James, Rice, Kenneth, Munroe, Patricia B., Morrison, Alanna C., Rao, Dabeeru C., Rotimi, Charles N., and Cupples, L. Adrienne
Abstract: The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene–smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.
Published: 2019
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20. Precision exercise medicine: understanding exercise response variability

Author: Ross, Robert, Goodpaster, Bret H, Koch, Lauren G, Sarzynski, Mark A, Kohrt, Wendy M, Johannsen, Neil M, Skinner, James S, Castro, Alex, Irving, Brian A, Noland, Robert C, Sparks, Lauren M, Spielmann, Guillaume, Day, Andrew G, Pitsch, Werner, Hopkins, William G, and Bouchard, Claude
Abstract: There is evidence from human twin and family studies as well as mouse and rat selection experiments that there are considerable interindividual differences in the response of cardiorespiratory fitness (CRF) and other cardiometabolic traits to a given exercise programme dose. We developed this consensus statement on exercise response variability following a symposium dedicated to this topic. There is strong evidence from both animal and human studies that exercise training doses lead to variable responses. A genetic component contributes to exercise training response variability.In this consensus statement, we (1) briefly review the literature on exercise response variability and the various sources of variations in CRF response to an exercise programme, (2) introduce the key research designs and corresponding statistical models with an emphasis on randomised controlled designs with or without multiple pretests and post-tests, crossover designs and repeated measures designs, (3) discuss advantages and disadvantages of multiple methods of categorising exercise response levels—a topic that is of particular interest for personalised exercise medicine and (4) outline approaches that may identify determinants and modifiers of CRF exercise response. We also summarise gaps in knowledge and recommend future research to better understand exercise response variability.
Published: 2019
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21. Convergence between biological, behavioural and genetic determinants of obesity

Author: Ghosh, Sujoy and Bouchard, Claude
Abstract: Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.
Published: 2017
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22. The Role of Eif6in Skeletal Muscle Homeostasis Revealed by Endurance Training Co-expression Networks

Author: Clarke, Kim, Ricciardi, Sara, Pearson, Tim, Bharudin, Izwan, Davidsen, Peter K., Bonomo, Michela, Brina, Daniela, Scagliola, Alessandra, Simpson, Deborah M., Beynon, Robert J., Khanim, Farhat, Ankers, John, Sarzynski, Mark A., Ghosh, Sujoy, Pisconti, Addolorata, Rozman, Jan, Hrabe de Angelis, Martin, Bunce, Chris, Stewart, Claire, Egginton, Stuart, Caddick, Mark, Jackson, Malcolm, Bouchard, Claude, Biffo, Stefano, and Falciani, Francesco
Abstract: Regular endurance training improves muscle oxidative capacity and reduces the risk of age-related disorders. Understanding the molecular networks underlying this phenomenon is crucial. Here, by exploiting the power of computational modeling, we show that endurance training induces profound changes in gene regulatory networks linking signaling and selective control of translation to energy metabolism and tissue remodeling. We discovered that knockdown of the mTOR-independent factor Eif6, which we predicted to be a key regulator of this process, affects mitochondrial respiration efficiency, ROS production, and exercise performance. Our work demonstrates the validity of a data-driven approach to understanding muscle homeostasis.
Published: 2017
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23. Abstract P205: Association of Angptl3/8 and 4/8 With Plasma Metabolites Before and After Exercise Training

Author: Dev, Prasun K, Miranda-Maravi, Sebastian, Hoffman, William, Barber, Jacob L, Schwartz, Charles S, Clarkson, William A, Robbins, Jeremy M, Rao, Prashant, Mi, Michael, Ghosh, Sujoy, Ghosh, Sujoy, Clish, Clary, Silbernagel, Gunther, Chen, Yan Q, Konrad, Robert J, Bouchard, Claude, Gerszten, Robert E, and Sarzynski, Mark A
Abstract: Introduction:Angiopoietin like protein (ANGPTL) complexes 3/8 and 4/8 are established inhibitors of lipoprotein lipase and modifiable by regular exercise. However, the molecular underpinning of these novel biomarkers has not been fully elucidated. The purpose of this study was to examine the associations between plasma metabolites and ANGPTL3/8 and 4/8 before and after exercise training.Methods:Measurements were taken before and after 20 weeks of exercise training in 630 adults (36% Black, 56% women, mean age 35 yrs) of the HERITAGE Family Study. Meso Scale Discovery immunoassays were used to measure ANGPTL3/8 and 4/8 in serum. Plasma metabolites (n=300 named) were measured using LC-MS and the HILIC-pos method. Linear mixed models tested the association between metabolites and each trait at baseline and post-training with full covariate adjustment. Significance was set to FDR<0.05.Results:A total of 111 and 93 metabolites were significantly associated with ANGPTL3/8 at baseline or post-training, respectively (Figure 1A). A total of 69 metabolites were associated with ANGPTL3/8 at both time points, including ketone bodies, acylcarnitines, and DMGV, while 24 metabolites were only associated at post-training including citric acid, methionine, and glycine. A total of 89 and 40 metabolites were significantly associated with ANGPTL4/8 at baseline or post-training, respectively (Figure 1B). A total of 13 metabolites were associated with ANGPTL4/8 at both time points including glycine and lysophospholipids, whereas 27 metabolites were associated only at post-training including hydroxyproline, N-Lignoceroyl Taurine, and methylguanidine.Conclusions:We identified several plasma metabolites associated with ANGPTL3/8 and 4/8 before and after exercise training. Our findings indicate potential metabolic pathways related to the exercise responsiveness of ANGPTL3/8 and 4/8, including glucose-alanine cycle, urea cycle, and glycine and methionine metabolism.
Published: 2023
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24. Abstract P201: Plasma Proteomic Signatures of Angptl3/8 and 4/8 Before and After Exercise Training

Author: Miranda-Maravi, Sebastian, Hoffman, William G, Dev, Prasun K, Barber, Jacob L, Schwartz, Charles S, Clarkson, William A, Robbins, Jeremy M, Rao, Prashant, Mi, Michael, Ghosh, Sujoy, Clish, Clary, Silbernagel, Gunther, Chen, Yan Q, Konrad, Robert J, Bouchard, Claude, Gerszten, Robert E, and Sarzynski, Mark A
Abstract: Introduction:Angiopoietin like protein (ANGPTL) complexes 3/8 and 4/8 are established inhibitors of lipoprotein lipase and modifiable by regular exercise. However, the molecular biomarkers related to their exercise responses have not been fully elucidated. The purpose of this study was to examine the associations between plasma proteins and ANGPTL3/8 and 4/8 before and after exercise training.Methods:Measurements were taken before and after 20 weeks of exercise training in 630 adults (36% Black, 56% women, mean age 35 yrs) of the HERITAGE Family Study. Meso Scale Discovery immunoassays were used to measure ANGPTL3/8 and ANGPTL4/8 complexes in serum. Plasma proteins (n=4979 aptamers) were quantified using SomaScan. Linear mixed models tested the association between plasma proteins and each trait at baseline and post- training with full covariate adjustment. Significance was set to FDR<0.05.Results:A total of 862 and 126 proteins were significantly associated with ANGPTL3/8 at baseline or post-training, respectively, with 80 proteins associated at both time points, including PCSK9 and PLTP (Figure 1A). Conversely, 46 proteins were only associated with ANGPTL3/8 at post-training, 23 of which whose levels significantly changed with training including NRP1, ghrelin, HHIP, and APOA1. A total of 433 and 71 proteins were significantly associated with ANGPTL4/8 at baseline or post-training, respectively, with 46 proteins associated with both time points (Figure 1B). A total of 25 proteins were only associated with ANGPTL4/8 at post-training, 12 of which whose levels significantly changed with training including ghrelin, COL6A2, and MMP16.Conclusions:We identified a subset of proteins uniquely associated with exercise-induced changes in ANGPTL3/8 and 4/8. Thus, the responsiveness of ANGPTL3/8 and 4/8 to regular exercise may be related to cholesterol esterification, lipoprotein remodeling, inflammatory response, and regulation of fibrinolysis and coagulation among other biological pathways.
Published: 2023
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25. Plasma Proteomic Kinetics in Response to Acute Exercise

Author: Mi, Michael Y., Barber, Jacob L., Rao, Prashant, Farrell, Laurie A., Sarzynski, Mark A., Bouchard, Claude, Robbins, Jeremy M., and Gerszten, Robert E.
Abstract: Regular exercise has many favorable effects on human health, which may be mediated in part by the release of circulating bioactive factors during each bout of exercise. Limited data exist regarding the kinetic responses of plasma proteins during and after acute exercise. Proteomic profiling of 4163 proteins was performed using a large-scale, affinity-based platform in 75 middle-aged adults who were referred for treadmill exercise stress testing. Plasma proteins were quantified at baseline, peak exercise, and 1-h postexercise, and those with significant changes at both exercise timepoints were further examined for their associations with cardiometabolic traits and change with aerobic exercise training in the HEalth, RIsk factors, exercise Training And GEnetics Family Study, a 20-week exercise intervention study. A total of 765 proteins changed (false discovery rate < 0.05) at peak exercise compared to baseline, and 128 proteins changed (false discovery rate < 0.05) at 1-h postexercise. The 56 proteins that changed at both timepoints included midkine, brain-derived neurotrophic factor, metalloproteinase inhibitor 4, and coiled-coil domain-containing protein 126 and were enriched for secreted proteins. The majority had concordant direction of change at both timepoints. Across all proteins assayed, gene set enrichment analysis showed increased abundance of coagulation-related proteins at 1-h postexercise. Forty-five proteins were associated with at least one measure of adiposity, lipids, glucose homeostasis, or cardiorespiratory fitness in HEalth, RIsk factors, exercise Training And GEnetics, and 20 proteins changed with aerobic exercise training. We identified hundreds of novel proteins that change during acute exercise, most of which resolved by 1 h into recovery. Proteins with sustained changes during exercise and recovery may be of particular interest as circulating biomarkers and pathways for further investigation in cardiometabolic diseases. These data will contribute to a biochemical roadmap of acute exercise that will be publicly available for the entire scientific community.
Published: 2023
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26. Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

Author: Liu, Chunyu, Kraja, Aldi T, Smith, Jennifer A, Brody, Jennifer A, Franceschini, Nora, Bis, Joshua C, Rice, Kenneth, Morrison, Alanna C, Lu, Yingchang, Weiss, Stefan, Guo, Xiuqing, Palmas, Walter, Martin, Lisa W, Chen, Yii-Der Ida, Surendran, Praveen, Drenos, Fotios, Cook, James P, Auer, Paul L, Chu, Audrey Y, Giri, Ayush, Zhao, Wei, Jakobsdottir, Johanna, Lin, Li-An, Stafford, Jeanette M, Amin, Najaf, Mei, Hao, Yao, Jie, Voorman, Arend, Larson, Martin G, Grove, Megan L, Smith, Albert V, Hwang, Shih-Jen, Chen, Han, Huan, Tianxiao, Kosova, Gulum, Stitziel, Nathan O, Kathiresan, Sekar, Samani, Nilesh, Schunkert, Heribert, Deloukas, Panos, Li, Man, Fuchsberger, Christian, Pattaro, Cristian, Gorski, Mathias, Kooperberg, Charles, Papanicolaou, George J, Rossouw, Jacques E, Faul, Jessica D, Kardia, Sharon L R, Bouchard, Claude, Raffel, Leslie J, Uitterlinden, André G, Franco, Oscar H, Vasan, Ramachandran S, O'Donnell, Christopher J, Taylor, Kent D, Liu, Kiang, Bottinger, Erwin P, Gottesman, Omri, Daw, E Warwick, Giulianini, Franco, Ganesh, Santhi, Salfati, Elias, Harris, Tamara B, Launer, Lenore J, Dörr, Marcus, Felix, Stephan B, Rettig, Rainer, Völzke, Henry, Kim, Eric, Lee, Wen-Jane, Lee, I-Te, Sheu, Wayne H-H, Tsosie, Krystal S, Edwards, Digna R Velez, Liu, Yongmei, Correa, Adolfo, Weir, David R, Völker, Uwe, Ridker, Paul M, Boerwinkle, Eric, Gudnason, Vilmundur, Reiner, Alexander P, van Duijn, Cornelia M, Borecki, Ingrid B, Edwards, Todd L, Chakravarti, Aravinda, Rotter, Jerome I, Psaty, Bruce M, Loos, Ruth J F, Fornage, Myriam, Ehret, Georg B, Newton-Cheh, Christopher, Levy, Daniel, and Chasman, Daniel I
Abstract: Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure–associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein–protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure–associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.
Published: 2016
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27. Understanding the Cellular and Molecular Mechanisms of Physical Activity-Induced Health Benefits.

Author: Neufer, P. Darrell, Bamman, Marcas M., Muoio, Deborah M., Bouchard, Claude, Cooper, Dan M., Goodpaster, Bret H., Booth, Frank W., Kohrt, Wendy M., Gerszten, Robert E., Mattson, Mark P., Hepple, Russell T., Kraus, William E., Reid, Michael B., Bodine, Sue C., Jakicic, John M., Fleg, Jerome L., Williams, John P., Joseph, Lyndon, Evans, Mary, and Maruvada, Padma
Abstract: The beneficial effects of physical activity (PA) are well documented, yet the mechanisms by which PA prevents disease and improves health outcomes are poorly understood. To identify major gaps in knowledge and potential strategies for catalyzing progress in the field, the NIH convened a workshop in late October 2014 entitled “Understanding the Cellular and Molecular Mechanisms of Physical Activity-Induced Health Benefits.” Presentations and discussions emphasized the challenges imposed by the integrative and intermittent nature of PA, the tremendous discovery potential of applying “-omics” technologies to understand interorgan crosstalk and biological networking systems during PA, and the need to establish an infrastructure of clinical trial sites with sufficient expertise to incorporate mechanistic outcome measures into adequately sized human PA trials. Identification of the mechanisms that underlie the link between PA and improved health holds extraordinary promise for discovery of novel therapeutic targets and development of personalized exercise medicine. [ABSTRACT FROM AUTHOR]
Published: 2015
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28. Cardiorespiratory fitness and brain volume and white matter integrity: The CARDIA Study.

Author: Zhu, Na, Jacobs Jr, David R, Schreiner, Pamela J, Launer, Lenore J, Whitmer, Rachel A, Sidney, Stephen, Demerath, Ellen, Thomas, William, Bouchard, Claude, He, Ka, Erus, Guray, Battapady, Harsha, Bryan, R Nick, and Jacobs, David R Jr
Published: 2015
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29. Cardiorespiratory fitness and brain volume and white matter integrity.

Author: Na Zhu, Jacobs, David R., Schreiner, Pamela J., Launer, Lenore J., Whitmer, Rachel A., Sidney, Stephen, Demerath, Ellen, Thomas, William, Bouchard, Claude, Ka He, Erus, Guray, Battapady, Harsha, and Bryan, R. Nick
Published: 2015
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30. Personalized Preventive Medicine: Genetics and the Response to Regular Exercise in Preventive Interventions.

Author: Bouchard, Claude, Antunes-Correa, Ligia M., Ashley, Euan A., Franklin, Nina, Hwang, Paul M., Mattsson, C. Mikael, Negrao, Carlos E., Phillips, Shane A., Sarzynski, Mark A., Wang, Ping-yuan, and Wheeler, Matthew T.
Abstract: Regular exercise and a physically active lifestyle have favorable effects on health. Several issues related to this theme are addressed in this report. A comment on the requirements of personalized exercise medicine and in-depth biological profiling along with the opportunities that they offer is presented. This is followed by a brief overview of the evidence for the contributions of genetic differences to the ability to benefit from regular exercise. Subsequently, studies showing that mutations in TP53 influence exercise capacity in mice and humans are succinctly described. The evidence for effects of exercise on endothelial function in health and disease also is covered. Finally, changes in cardiac and skeletal muscle in response to exercise and their implications for patients with cardiac disease are summarized. Innovative research strategies are needed to define the molecular mechanisms involved in adaptation to exercise and to translate them into useful clinical and public health applications. [ABSTRACT FROM AUTHOR]
Published: 2015
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31. Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Author: Kanoni, Stavroula, Graham, Sarah E., Wang, Yuxuan, Surakka, Ida, Ramdas, Shweta, Zhu, Xiang, Clarke, Shoa L., Bhatti, Konain Fatima, Vedantam, Sailaja, Winkler, Thomas W., Locke, Adam E., Marouli, Eirini, Zajac, Greg J. M., Wu, Kuan-Han H., Ntalla, Ioanna, Hui, Qin, Klarin, Derek, Hilliard, Austin T., Wang, Zeyuan, Xue, Chao, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F., Holm, Hilma, Olafsson, Isleifur, Hwang, Mi Yeong, Han, Sohee, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M., Rasheed, Humaira, Havulinna, Aki S., Veturi, Yogasudha, Pacheco, Jennifer Allen, Rosenthal, Elisabeth A., Lingren, Todd, Feng, QiPing, Kullo, Iftikhar J., Narita, Akira, Takayama, Jun, Martin, Hilary C., Hunt, Karen A., Trivedi, Bhavi, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E., Campbell, Archie, Lin, Kuang, Millwood, Iona Y., Rasheed, Asif, Hindy, George, Faul, Jessica D., Zhao, Wei, Weir, David R., Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Choudhury, Ananyo, Sengupta, Dhriti, Mahajan, Anubha, Brown, Michael R., Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M., Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian’an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Wood, Andrew R., Ji, Yingji, Gao, Zishan, Haworth, Simon, Yousri, Noha A., Mitchell, Ruth E., Chai, Jin Fang, Aadahl, Mette, Bjerregaard, Anne A., Yao, Jie, Manichaikul, Ani, Hwu, Chii-Min, Hung, Yi-Jen, Warren, Helen R., Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L., Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Mauro, Pala, Matteo, Floris, McDaid, Aaron F., Marques-Vidal, Pedro, Wielscher, Matthias, Trompet, Stella, Sattar, Naveed, Møllehave, Line T., Munz, Matthias, Zeng, Lingyao, Huang, Jianfeng, Yang, Bin, Poveda, Alaitz, Kurbasic, Azra, Lamina, Claudia, Forer, Lukas, Scholz, Markus, Galesloot, Tessel E., Bradfield, Jonathan P., Ruotsalainen, Sanni E., Daw, EWarwick, Zmuda, Joseph M., Mitchell, Jonathan S., Fuchsberger, Christian, Christensen, Henry, Brody, Jennifer A., Vazquez-Moreno, Miguel, Feitosa, Mary F., Wojczynski, Mary K., Wang, Zhe, Preuss, Michael H., Mangino, Massimo, Christofidou, Paraskevi, Verweij, Niek, Benjamins, Jan W., Engmann, Jorgen, Tsao, Noah L., Verma, Anurag, Slieker, Roderick C., Lo, Ken Sin, Zilhao, Nuno R., Le, Phuong, Kleber, Marcus E., Delgado, Graciela E., Huo, Shaofeng, Ikeda, Daisuke D., Iha, Hiroyuki, Yang, Jian, Liu, Jun, Demirkan, Ayşe, Leonard, Hampton L., Marten, Jonathan, Frank, Mirjam, Schmidt, Börge, Smyth, Laura J., Cañadas-Garre, Marisa, Wang, Chaolong, Nakatochi, Masahiro, Wong, Andrew, Hutri-Kähönen, Nina, Sim, Xueling, Xia, Rui, Huerta-Chagoya, Alicia, Fernandez-Lopez, Juan Carlos, Lyssenko, Valeriya, Nongmaithem, Suraj S., Bayyana, Swati, Stringham, Heather M., Irvin, Marguerite R., Oldmeadow, Christopher, Kim, Han-Na, Ryu, Seungho, Timmers, Paul R. H. J., Arbeeva, Liubov, Dorajoo, Rajkumar, Lange, Leslie A., Prasad, Gauri, Lorés-Motta, Laura, Pauper, Marc, Long, Jirong, Li, Xiaohui, Theusch, Elizabeth, Takeuchi, Fumihiko, Spracklen, Cassandra N., Loukola, Anu, Bollepalli, Sailalitha, Warner, Sophie C., Wang, Ya Xing, Wei, Wen B., Nutile, Teresa, Ruggiero, Daniela, Sung, Yun Ju, Chen, Shufeng, Liu, Fangchao, Yang, Jingyun, Kentistou, Katherine A., Banas, Bernhard, Nardone, Giuseppe Giovanni, Meidtner, Karina, Bielak, Lawrence F., Smith, Jennifer A., Hebbar, Prashantha, Farmaki, Aliki-Eleni, Hofer, Edith, Lin, Maoxuan, Concas, Maria Pina, Vaccargiu, Simona, van der Most, Peter J., Pitkänen, Niina, Cade, Brian E., van der Laan, Sander W., Chitrala, Kumaraswamy Naidu, Weiss, Stefan, Bentley, Amy R., Doumatey, Ayo P., Adeyemo, Adebowale A., Lee, Jong Young, Petersen, Eva R. B., Nielsen, Aneta A., Choi, Hyeok Sun, Nethander, Maria, Freitag-Wolf, Sandra, Southam, Lorraine, Rayner, Nigel W., Wang, Carol A., Lin, Shih-Yi, Wang, Jun-Sing, Couture, Christian, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Cuellar-Partida, Gabriel, Vestergaard, Henrik, Hidalgo, Bertha, Giannakopoulou, Olga, Cai, Qiuyin, Obura, Morgan O., van Setten, Jessica, Li, Xiaoyin, Liang, Jingjing, Tang, Hua, Terzikhan, Natalie, Shin, Jae Hun, Jackson, Rebecca D., Reiner, Alexander P., Martin, Lisa Warsinger, Chen, Zhengming, Li, Liming, Kawaguchi, Takahisa, Thiery, Joachim, Bis, Joshua C., Launer, Lenore J., Li, Huaixing, Nalls, Mike A., Raitakari, Olli T., Ichihara, Sahoko, Wild, Sarah H., Nelson, Christopher P., Campbell, Harry, Jäger, Susanne, Nabika, Toru, Al-Mulla, Fahd, Niinikoski, Harri, Braund, Peter S., Kolcic, Ivana, Kovacs, Peter, Giardoglou, Tota, Katsuya, Tomohiro, de Kleijn, Dominique, de Borst, Gert J., Kim, Eung Kweon, Adams, Hieab H. H., Ikram, M. Arfan, Zhu, Xiaofeng, Asselbergs, Folkert W., Kraaijeveld, Adriaan O., Beulens, Joline W. J., Shu, Xiao-Ou, Rallidis, Loukianos S., Pedersen, Oluf, Hansen, Torben, Mitchell, Paul, Hewitt, Alex W., Kähönen, Mika, Pérusse, Louis, Bouchard, Claude, Tönjes, Anke, Chen, Yii-Der Ida, Pennell, Craig E., Mori, Trevor A., Lieb, Wolfgang, Franke, Andre, Ohlsson, Claes, Mellström, Dan, Cho, Yoon Shin, Lee, Hyejin, Yuan, Jian-Min, Koh, Woon-Puay, Rhee, Sang Youl, Woo, Jeong-Taek, Heid, Iris M., Stark, Klaus J., Zimmermann, Martina E., Völzke, Henry, Homuth, Georg, Evans, Michele K., Zonderman, Alan B., Polasek, Ozren, Pasterkamp, Gerard, Hoefer, Imo E., Redline, Susan, Pahkala, Katja, Oldehinkel, Albertine J., Snieder, Harold, Biino, Ginevra, Schmidt, Reinhold, Schmidt, Helena, Bandinelli, Stefania, Dedoussis, George, Thanaraj, Thangavel Alphonse, Kardia, Sharon L. R., Peyser, Patricia A., Kato, Norihiro, Schulze, Matthias B., Girotto, Giorgia, Böger, Carsten A., Jung, Bettina, Joshi, Peter K., Bennett, David A., De Jager, Philip L., Lu, Xiangfeng, Mamakou, Vasiliki, Brown, Morris, Caulfield, Mark J., Munroe, Patricia B., Guo, Xiuqing, Ciullo, Marina, Jonas, Jost B., Samani, Nilesh J., Kaprio, Jaakko, Pajukanta, Päivi, Tusié-Luna, Teresa, Aguilar-Salinas, Carlos A., Adair, Linda S., Bechayda, Sonny Augustin, de Silva, H. Janaka, Wickremasinghe, Ananda R., Krauss, Ronald M., Wu, Jer-Yuarn, Zheng, Wei, Hollander, Anneke Iden, Bharadwaj, Dwaipayan, Correa, Adolfo, Wilson, James G., Lind, Lars, Heng, Chew-Kiat, Nelson, Amanda E., Golightly, Yvonne M., Wilson, James F., Penninx, Brenda, Kim, Hyung-Lae, Attia, John, Scott, Rodney J., Rao, D. C., Arnett, Donna K., Hunt, Steven C., Walker, Mark, Koistinen, Heikki A., Chandak, Giriraj R., Mercader, Josep M., Costanzo, Maria C., Jang, Dongkeun, Burtt, Noël P., Villalpando, Clicerio Gonzalez, Orozco, Lorena, Fornage, Myriam, Tai, EShyong, van Dam, Rob M., Lehtimäki, Terho, Chaturvedi, Nish, Yokota, Mitsuhiro, Liu, Jianjun, Reilly, Dermot F., McKnight, Amy Jayne, Kee, Frank, Jöckel, Karl-Heinz, McCarthy, Mark I., Palmer, Colin N. A., Vitart, Veronique, Hayward, Caroline, Simonsick, Eleanor, van Duijn, Cornelia M., Jin, Zi-Bing, Qu, Jia, Hishigaki, Haretsugu, Lin, Xu, März, Winfried, Gudnason, Vilmundur, Tardif, Jean-Claude, Lettre, Guillaume, Hart, Leen M.‘t, Elders, Petra J. M., Damrauer, Scott M., Kumari, Meena, Kivimaki, Mika, van der Harst, Pim, Spector, Tim D., Loos, Ruth J. F., Province, Michael A., Parra, Esteban J., Cruz, Miguel, Psaty, Bruce M., Brandslund, Ivan, Pramstaller, Peter P., Rotimi, Charles N., Christensen, Kaare, Ripatti, Samuli, Widén, Elisabeth, Hakonarson, Hakon, Grant, Struan F. A., Kiemeney, Lambertus A. L. M., de Graaf, Jacqueline, Loeffler, Markus, Kronenberg, Florian, Gu, Dongfeng, Erdmann, Jeanette, Schunkert, Heribert, Franks, Paul W., Linneberg, Allan, Jukema, J. Wouter, Khera, Amit V., Männikkö, Minna, Jarvelin, Marjo-Riitta, Kutalik, Zoltan, Francesco, Cucca, Mook-Kanamori, Dennis O., van Dijk, Ko Willems, Watkins, Hugh, Strachan, David P., Grarup, Niels, Sever, Peter, Poulter, Neil, Chuang, Lee-Ming, Rotter, Jerome I., Dantoft, Thomas M., Karpe, Fredrik, Neville, Matt J., Timpson, Nicholas J., Cheng, Ching-Yu, Wong, Tien-Yin, Khor, Chiea Chuen, Li, Hengtong, Sabanayagam, Charumathi, Peters, Annette, Gieger, Christian, Hattersley, Andrew T., Pedersen, Nancy L., Magnusson, Patrik K. E., Boomsma, Dorret I., Willemsen, Allegonda H. M., Cupples, LAdrienne, van Meurs, Joyce B. J., Ghanbari, Mohsen, Gordon-Larsen, Penny, Huang, Wei, Kim, Young Jin, Tabara, Yasuharu, Wareham, Nicholas J., Langenberg, Claudia, Zeggini, Eleftheria, Kuusisto, Johanna, Laakso, Markku, Ingelsson, Erik, Abecasis, Goncalo, Chambers, John C., Kooner, Jaspal S., de Vries, Paul S., Morrison, Alanna C., Hazelhurst, Scott, Ramsay, Michèle, North, Kari E., Daviglus, Martha, Kraft, Peter, Martin, Nicholas G., Whitfield, John B., Abbas, Shahid, Saleheen, Danish, Walters, Robin G., Holmes, Michael V., Black, Corri, Smith, Blair H., Baras, Aris, Justice, Anne E., Buring, Julie E., Ridker, Paul M., Chasman, Daniel I., Kooperberg, Charles, Tamiya, Gen, Yamamoto, Masayuki, van Heel, David A., Trembath, Richard C., Wei, Wei-Qi, Jarvik, Gail P., Namjou, Bahram, Hayes, M. Geoffrey, Ritchie, Marylyn D., Jousilahti, Pekka, Salomaa, Veikko, Hveem, Kristian, Åsvold, Bjørn Olav, Kubo, Michiaki, Kamatani, Yoichiro, Okada, Yukinori, Murakami, Yoshinori, Kim, Bong-Jo, Thorsteinsdottir, Unnur, Stefansson, Kari, Zhang, Jifeng, Chen, YEugene, Ho, Yuk-Lam, Lynch, Julie A., Rader, Daniel J., Tsao, Philip S., Chang, Kyong-Mi, Cho, Kelly, O’Donnell, Christopher J., Gaziano, John M., Wilson, Peter W. F., Frayling, Timothy M., Hirschhorn, Joel N., Kathiresan, Sekar, Mohlke, Karen L., Sun, Yan V., Morris, Andrew P., Boehnke, Michael, Brown, Christopher D., Natarajan, Pradeep, Deloukas, Panos, Willer, Cristen J., Assimes, Themistocles L., and Peloso, Gina M.
Abstract: Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N= 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.
Published: 2022
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32. Abstract 15316: Associations Between Plasma Proteins With Body Composition Traits and Their Responses to Exercise Training

Author: Clarkson, William A, Barber, Jacob L, Robbins, Jeremy M, Cai, Guoshuai, Rao, Prashant, Mi, Michael, Dev, Prasun, Ghosh, Sujoy, Katz, Daniel H, Clish, Clary, Bouchard, Claude, Sarzynski, Mark A, and Gerszten, Robert E
Abstract: Introduction:Although exercise training is known to alter body composition, the molecular biomarkers and mechanisms related to these changes have not been fully elucidated. The purpose of this study was to examine the associations between plasma proteins and body composition traits before and after exercise training.Methods:Measurements were taken before and after 20 weeks of standardized, endurance training in self-identified Black and White adults of the HERITAGE Family Study (n=647). Plasma proteins were measured using an affinity-based platform (n=4979 aptamers). 11 body composition traits were measured using underwater weighing, CT scans, and anthropometry: BMI, body surface area, fat mass, fat free mass, %fat, waist circumference, waist-to-hip ratio, body weight, and abdominal visceral, subcutaneous, and total fat. Linear mixed models were used to test the association between plasma proteins and each trait at baseline and in response to training with full covariate adjustment (Table 1). Significance was set to FDR<0.05.Results:On average, subjects were [mean and (SD)] 35 (14) years old, 33% Black, 54% female, and had BMI 26.2 (5.2) kg/m2. The number of significant associations between proteins and traits at baseline and in response to exercise training ranged from 645-1714 and 0-42, respectively (Table 1). While leptin was among the top associated proteins at both time points for almost all traits, our analysis revealed many novel associations between changes in proteins with changes in body composition. Changes in DLK-1 significantly associated with changes in 9 of 11 traits but was not associated with baseline measures.Conclusions:Numerous plasma proteins were associated with body composition traits at baseline, with fewer associated with trait responses to training. Notably, we identified a subset of proteins uniquely associated with exercise-induced changes in body composition traits.
Published: 2022
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33. Abstract 13353: Association of Plasma Metabolites With Inflammatory Markers CRP and GlycA and Their Responses to Exercise Training

Author: Hoffmann, William G, Barber, Jacob L, Dev, Prasun, Clarkson, William A, Cai, Guoshuai, Rao, Prashant, Mi, Michael, Katz, Daniel H, Ghosh, Sujoy, Clish, Clary, Robbins, Jeremy M, Bouchard, Claude, Gerszten, Robert E, and Sarzynski, Mark A
Abstract: Introduction.C-reactive protein (CRP) and GlycA are established biomarkers of inflammation. Regular exercise tends to decrease CRP and GlycA levels. However, the spectrum of molecules associated with the anti-inflammatory effects of regular exercise are less well understood. Hypothesis.We hypothesized that distinct metabolite signatures exist for both baseline levels and exercise responsiveness of CRP and GlycA. Methods.Measures were performed before and after 20 weeks of endurance exercise training in 652 Black and White adults from the HERITAGE Family Study. A total of 300 targeted plasma metabolites were measured using LC-MS. High-sensitivity CRP and GlycA were measured using automated assays and NMR spectroscopy (LabCorp), respectively. Linear mixed models were used to test: 1) Association of baselinemetabolites with baselinehsCRP and GlycA and 2) Association of changesin metabolite with changesin hsCRP and GlycA. Models were adjusted for age, sex, race, BMI, with family membership as a random variable, with change models also adjusting for baseline trait value. Significance was determined as FDR<0.05. Results.Baseline levels and changes of hsCRP and GlycA were moderately correlated (r=0.51 and 0.31, p<0.0001 for both, respectively). At baseline, 40 and 94 metabolites were associated with hsCRP and GlycA, respectively, with 30 metabolites associated with both phenotypes. The top baseline associations for both traits included multiple species of lysophosphatidylcholine (LPC) and phosphatidylethanolamine (PE), while cortisol, biliverdin, and bilirubin were among the metabolites associated with GlycA only. The changes in only one metabolite were associated with concomitant changes in CRP, while no associations were found for change in GlycA. Conclusions.Plasma metabolite associations with baseline hsCRP overlapped with those associated with baseline GlycA levels. Several unique metabolite associations with baseline GlycA were identified, including molecules in established inflammatory pathways. Metabolite changes with exercise were not associated with changes in either measure. These findings have implications for the use of metabolites as signatures of systemic inflammation vs as targets of lifestyle interventions.
Published: 2022
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34. Abstract 10710: Plasma Proteomic Profiles of the Blood Pressure Response During Exercise Are Associated With Incident Hypertension

Author: Rao, Prashant, Keyes, Michelle, Mi, Michael, Barber, Jacob, Tahir, Usman A, Deng, Shuliang, Clish, Clary, Shen, Dongxiao, Farrell, Laurie, Xanthakis, Vanessa, Ramachandran, Vasan S, Bouchard, Claude, Sarzynski, Mark A, Gerszten, Robert E, and Robbins, Jeremy
Abstract: Introduction:The blood pressure (BP) response during acute exercise (acute exercise blood pressure (AEBP)) is related to future risk of hypertension (HTN) and cardiovascular disease (CVD). Biochemical characterization of AEBP could identify novel biomarkers of CVD risk and inform understanding of its biology.Methods:We applied an aptamer-based proteomics platform to assay ~5000 proteins at rest in 681 healthy individuals of the HERITAGE Family Study (mean age 34y, 54% women) who underwent an acute exercise perturbation. AEBP was measured during submaximal exercise on a cycle ergometer. We then performed a proteomic association study of resting BP and AEBP. Top protein associations with acute exercise SBP and DBP were analyzed for their association with incident HTN and CVD in the Framingham Heart Study (FHS). Putative causal effects of AEBP-related proteins were investigated by Mendelian randomization (MR), using cis-protein quantitative loci genetic instruments.Results:We identified new markers of AEBP, many of which are secreted proteins that span biological processes relevant to vascular function including transforming-growth factor beta-receptor 3 (β = -3.39, p = 2.33e-6), prostaglandin D2-synthase (β = -2.50, p = 1.18e-10-9), and angiopoietin-related protein 4 (β = 2.44, p = 1.05e-4). The addition of 12 AEBP-associated proteins to clinical information informed future risk of HTN and CVD among normotensive community-dwelling individuals (clinical model, clinical proteomic model AUCs: incident HTN 0.69, 0.73; coronary heart disease 0.73, 0.76; heart failure 0.83, 0.87). MR analysis of AEBP-associated proteins supported a potential causal relationship between 5 proteins and BP regulation (TGFBR3, ANGPTL4, CGA FSHB, PTGDS, KLK8).Conclusions:We identified new blood biomarkers of BP regulation that were elicited only by an acute exercise perturbation and highlight novel potential causal pathways.
Published: 2022
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35. Abstract 13514: Associations Between Plasma Metabolites With Body Composition Traits and Their Responses to Exercise Training

Author: Dev, Prasun, Barber, Jacob L, Clarkson, William A, Robbins, Jeremy M, Rao, Prashant, Mi, Michael, Ghosh, Sujoy, Katz, Daniel H, Clish, Clary, Bouchard, Claude, Gerszten, Robert E, and Sarzynski, Mark A
Abstract: INTRODUCTION:Although exercise training can improve body composition, the molecular biomarkers and mechanisms related to these changes have not been fully elucidated.HYPOTHESIS:We hypothesized that distinct metabolite signatures exist for both baseline levels and exercise responsiveness of body composition traits, with substantial overlap across traits.METHODS:Measurements were taken before and after 20 weeks of endurance training in self-identified Black and White adults of the HERITAGE Family Study (n=652). 300 targeted plasma metabolites were measured using LC-MS. Underwater weighing, CT scans, and anthropometric measurements were used to derive the 11 body composition traits included in this study: BMI, body surface area, fat mass, fat free mass, %fat, waist circumference, waist-to-hip ratio, body weight, and abdominal visceral, subcutaneous, and total fat. Linear mixed models were used to test the association between plasma metabolites and each body composition trait at baseline and in response to training with full covariate adjustment. Significance was set to FDR<0.05.Results:On average, subjects were [mean and (SD)] 35 (14) years old, 33% Black, 54% female, and had BMI of 26.2 (5.2) kg/m2. The number of metabolites significantly associated with body composition traits at baseline ranged from 57-141 (Table 1). DMGV was among the top 3 associated metabolites at baseline for all 11 traits, while SM(d18:1/16:1) was associated with 8 of 11 baseline traits. Few if any significant associations were found between change in metabolites and change in body composition measures in response to exercise training (range: 0-10) (Table 1).CONCLUSIONS:Although numerous metabolites were associated with body composition traits at baseline, few associations were observed with trait responses to training. These results suggest that intrinsic body composition and its response to exercise training may have differing underlying metabolic signatures.
Published: 2022
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36. Abstract 15399: Proteomic Landscape of Plasma Lipoprotein Responses to Regular Exercise

Author: Barber, Jacob L, Cai, Guoshuai, Robbins, Jeremy M, Rao, Prashant, Mi, Michael, Ghosh, Sujoy, Clish, Clary, Katz, Daniel H, Bouchard, Claude, Gerszten, Robert E, and Sarzynski, Mark A
Abstract: Introduction:Lipoproteins are among the strongest predictors of CVD and are altered through regular exercise. However, the molecular changes underlying the potential benefits of exercise on plasma lipoproteins are unclear.Methods:Proteins (n=4979) were quantified from the plasma of 647 Black and White adults (56% women, mean age = 34.9 yrs) before and after 20-weeks of endurance exercise training using SomaScan. All subjects had complete data for 7 lipoprotein traits that improved with training: HDL-C, TG, large TG rich lipoprotein particles (LTRLP), small LDL particles (SLDLP), large HDL particles (LHDLP), TRLP size, and LDLP size. Fully adjusted linear mixed models were used to test the association of 1) baseline proteins with baseline lipoproteins and 2) delta proteins with delta lipoproteins (delta = post training - baseline value). Significance was determined as FDR<0.05.Results:We identified numerous proteins associated with baseline levels of at least one of the seven lipoprotein traits (range: 48-1099) and whose changes in response to regular exercise were associated with concomitant changes in lipoproteins (range: 4-95) (Table 1). Substantial overlap was found between proteins associated with lipoproteins across timepoints, with 16 proteins associated with 4 or more lipoprotein traits at both timepoints. Plasma abundance of 12/16 proteins significantly changed with training (FDR <0.05). Additionally, for these proteins plasma abundance changed in concordance with the beneficial direction of the associated lipoprotein trait (e.g., proteins associated with atheroprotective lipoprotein traits increased with training and proteins associated with atherogenic traits decreased).Conclusions:Beneficial alterations to plasma lipoproteins with regular exercise are reflected in changes to the plasma proteome. Proteins identified here may represent novel markers of the benefits of regular exercise and of systemic lipoprotein metabolism.
Published: 2022
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37. Abstract 13308: Complementary Investigations of Plasma Proteomics Identify Novel Protein Associations With Incident Diabetes and Glucose Metabolism

Author: Mi, Michael Y, Cronje, Helene T, Austin, Thomas R, Biggs, Mary L, Siscovick, David S, Lemaitre, Rozenn N, Psaty, Bruce M, Tracy, Russell P, Djousse, Luc, Kizer, Jorge R, IX, Joachim H, Sotoodehnia, Nona, Rao, Prashant, Robbins, Jeremy M, Barber, Jacob L, Sarzynski, Mark A, Clish, Clary, Bouchard, Claude, Mukamal, Ken J, Jensen, Majken K, and Gerszten, Robert E
Abstract: Introduction:Type 2 diabetes (T2D) is a cardiovascular disease risk equivalent and likely results from broad metabolic changes, which high throughput proteomics have helped to unravel. Prior studies are limited by proteomic coverage, cross sectional design, and lack of physiologic phenotyping.Hypothesis:Complementary proteomic studies of incident T2D and physiologic responses to an intravenous glucose tolerance test (IVGTT) will identify novel proteins with roles in glucose homeostasis and future risk of T2D.Methods:Cardiovascular Health Study (CHS) and HERITAGE study participants without diabetes underwent SomaScan®profiling of 4,776 plasma proteins. HERITAGE participants underwent IVGTT, from which insulin sensitivity index (SI), acute insulin response to glucose (AIRG), and glucose effectiveness (SG) were derived. We used Cox regression to test protein associations with 18-year incident T2D in CHS, and multivariable linear regression to test protein associations with IVGTT measures in HERITAGE.Results:In CHS (N = 2631, 74 ± 5 years, 62% female, 14% Black), 57 proteins were significantly associated with incident T2D after comprehensive covariate and multiple testing adjustment. Of these, 44, 9, and 8 were associated with SI, AIRG, and SGrespectively in HERITAGE (N = 752, 35 ± 14 years, 55% female, 38% Black) (Figure). Notable findings include beta-glucuronidase, which associated with increased T2D risk (HR 1.46 per SD increase in log2protein level) and lower SG, suggesting a role in insulin-independent glucose disposal, and thrombospondin-2, which associated with increased T2D risk (HR 1.26 per SD), lower AIRG, and not with SI, indicating that it may be a marker of pancreatic dysfunction.Conclusions:By integrating proteomics from two complementary prospective cohorts using different but related outcomes, we identified 34 novel protein-T2D associations, and characterized their relationship with physiologic axes of glucose metabolism.
Published: 2022
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38. Abstract 15168: Plasma Metabolomic Profiling Identifies Markers of Cardiorespiratory Fitness Responsive to Endurance Exercise Training

Author: Rao, Prashant, Mi, Michael, Barber, Jacob, Deng, Shuliang, Farrell, Laurie, Bouchard, Claude, Clish, Clary, Sarzynski, Mark A, Gerszten, Robert E, and Robbins, Jeremy
Abstract: Background:High-throughput metabolite profiling allows for the assessment of thousands of metabolites that may participate in exercise-related pathways. Here, we characterize plasma metabolite changes in healthy individuals undergoing endurance exercise training (ET) to identify biochemical features of VO2max and/or those responsive to ET.Methods:We measured 444 known metabolites and 3221 non-targeted metabolite peaks using liquid chromatography tandem mass spectrometry and VO2max using CPET before and after 20 weeks of supervised, endurance ET in 654 sedentary participants (mean age=34y; 39% self-identified Black) from the HERITAGE Study. Multivariate linear regression assessed the relation between metabolites and baseline VO2max (ml·kg–1·min–1), adjusting for age, sex, and race. Changes after ET were determined using paired ttests. We used a false discovery rate (q) <0.05 to determine statistical significance.Results:494 metabolites were associated with VO2max, the majority (375/494) of which were non-targeted (unknown) metabolites with greater effect sizes than targeted peaks [β range: -29.66 - 17.80 and -22.76 - 12.87 for unknown and known metabolites]. We recapitulated known metabolite associations with VO2max including DMGV, branched chain amino acids, and uric acid (Figure 1). 110 of 560 metabolites that changed after ET were associated with VO2max, including non-targeted peaks that concordantly changed after ET (e.g. metabolite peaks positively associated with VO2max that increased with ET; m/z385.3056 and 695.5086; β for VO2max = 9.82 and -19.33, q= 5.56e-7 and 2.61e-17, and log fold-change = 0.03 and -0.01, q=9.58e-13 and 1.93e-4, respectively).Conclusions:We identified novel metabolite peaks associated with VO2max that concordantly changed after ET. Non-targeted metabolomic profiling reveals new markers related to VO2max and exercise response, motivating ongoing work to unambiguously identify these compounds.
Published: 2022
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39. Association of Fitness in Young Adulthood With Survival and Cardiovascular Risk: The Coronary Artery Risk Development in Young Adults (CARDIA) Study

Author: Shah, Ravi V., Murthy, Venkatesh L., Colangelo, Laura A., Reis, Jared, Venkatesh, Bharath Ambale, Sharma, Ravi, Abbasi, Siddique A., Goff, David C., Carr, J. Jeffrey, Rana, Jamal S., Terry, James G., Bouchard, Claude, Sarzynski, Mark A., Eisman, Aaron, Neilan, Tomas, Das, Saumya, Jerosch-Herold, Michael, Lewis, Cora E., Carnethon, Mercedes, Lewis, Gregory D., and Lima, Joao A. C.
Abstract: IMPORTANCE: Although cardiorespiratory fitness (CRF) is prognostic in older adults, the effect of CRF during early adulthood on long-term cardiovascular structure, function, and prognosis is less clear. OBJECTIVE: To examine whether CRF in young adults is associated with long-term clinical outcome and subclinical cardiovascular disease (CVD). DESIGN, SETTING, AND PARTICIPANTS: Prospective study of 4872 US adults aged 18 to 30 years who underwent treadmill exercise testing at a baseline study visit from March 25, 1985, to June 7, 1986, and 2472 individuals who underwent a second treadmill test 7 years later. Median follow-up was 26.9 years, with assessment of obesity, left ventricular mass and strain, coronary artery calcification (CAC), and vital status and incident CVD. Follow-up was complete on August 31, 2011, and data were analyzed from recruitment through the end of follow-up. MAIN OUTCOMES AND MEASURES: The presence of CAC was assessed by computed tomography at years 15 (2000-2001), 20 (2005-2006), and 25 (2010-2011), and left ventricular mass was assessed at years 5 (1990-1991) and 25 (with global longitudinal strain). Incident CVD and all-cause mortality were adjudicated. RESULTS: Of the 4872 individuals, 273 (5.6%) died and 193 (4.0%) experienced CVD events during follow-up. After comprehensive adjustment, each additional minute of baseline exercise test duration was associated with a 15% lower hazard of death (hazard ratio [HR], 0.85; 95% CI, 0.80-0.91; P < .001) and a 12% lower hazard of CVD (HR, 0.88; 95% CI, 0.81-0.96; P = .002). Higher levels of baseline CRF were associated with significantly lower left ventricular mass index (β = −0.24; 95% CI, −0.45 to −0.03; P = .02) and significantly better lobal longitudinal strain (β = −0.09; 95% CI, −0.14 to −0.05; P < .001) at year 25. Fitness was not associated with CAC. A 1-minute reduction in fitness by year 7 was associated with 21% and 20% increased hazards of death (HR, 1.21; 95% CI, 1.07-1.37; P = .002) and CVD (HR, 1.20; 95% CI, 1.06-1.37; P = .006), respectively, along with a more impaired strain (β = 0.15; 95% CI, 0.08-0.23; P < .001). No association between change in fitness and CAC was found. CONCLUSIONS AND RELEVANCE: Higher levels of fitness at baseline and improvement in fitness early in adulthood are favorably associated with lower risks for CVD and mortality. Fitness and changes in fitness are associated with myocardial hypertrophy and dysfunction but not CAC. Regular efforts to ascertain and improve CRF in young adulthood may play a critical role in promoting cardiovascular health and interrupting early CVD pathogenesis.
Published: 2016
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40. Less Sitting, More Physical Activity, or Higher Fitness?

Author: Bouchard, Claude, Blair, Steven N., and Katzmarzyk, Peter T.
Abstract: Epidemiological studies have found that time spent in sedentary behaviors, levels of physical activity, and cardiorespiratory fitness are all associated with mortality rates. They are also related to the risks of obesity, type 2 diabetes mellitus, hypertension, cardiovascular disease, aging-associated frailty, and cancer. The evidence is such that the National Institutes of Health recently launched a new Common Fund initiative aimed at identifying the molecular transducers of adaptation to physical activity in various tissues and organs. It has been estimated that 9.4% of all 57 million deaths in the world in 2008 could be attributed to physical inactivity, which translates into more than 5 million deaths worldwide. Physical inactivity has a deleterious effect that is comparable to smoking and obesity. Importantly, this global estimate relates to levels of physical activity and does not take into account sedentary behavior and cardiorespiratory fitness. Currently, there are national and international guidelines for physical activity level that are highly concordant. The weekly recommendations include 150 minutes of moderate-intensity activity, 75 minutes of vigorous-intensity activity, or some combination of moderate and vigorous activity with 2 days of resistance exercise. However, these guidelines offer no recommendations regarding sedentary time or goals for cardiorespiratory fitness levels. It will be increasingly important for disease prevention, successful aging, and reduction of premature mortality to broaden the focus of the public health message to include not only more physical activity but also less sitting and higher cardiorespiratory fitness. We briefly review the evidence and discuss key issues to be addressed to make this approach a reality.
Published: 2015
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41. Cardiorespiratory fitness and cognitive function in middle age: the CARDIA study.

Author: Zhu, Na, Jacobs Jr, David R, Schreiner, Pamela J, Yaffe, Kristine, Bryan, Nick, Launer, Lenore J, Whitmer, Rachel A, Sidney, Stephen, Demerath, Ellen, Thomas, William, Bouchard, Claude, He, Ka, Reis, Jared, Sternfeld, Barbara, and Jacobs, David R Jr
Published: 2014
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42. Cardiorespiratory fitness and cognitive function in middle age.

Author: Zhu, Na, Jacobs Jr.,, David R., Schreiner, Pamela J., Yaffe, Kristine, Bryan, Nick, Launer, Lenore J., Whitmer, Rachel A., Sidney, Stephen, Demerath, Ellen, Thomas, William, Bouchard, Claude, He, Ka, Reis, Jared, and Sternfeld, Barbara
Published: 2014
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43. 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., and Soukas, Alexander A.
Abstract: Summary: The transcriptional coactivator peroxisome proliferator-activated receptor-gamma coactivator-1α (PGC-1α) regulates metabolic genes in skeletal muscle and contributes to the response of muscle to exercise. Muscle PGC-1α transgenic expression and exercise both increase the expression of thermogenic genes within white adipose. How the PGC-1α-mediated response to exercise in muscle conveys signals to other tissues remains incompletely defined. We employed a metabolomic approach to examine metabolites secreted from myocytes with forced expression of PGC-1α, and identified β-aminoisobutyric acid (BAIBA) as a small molecule myokine. BAIBA increases the expression of brown adipocyte-specific genes in white adipocytes and β-oxidation in hepatocytes both in vitro and in vivo through a PPARα-mediated mechanism, induces a brown adipose-like phenotype in human pluripotent stem cells, and improves glucose homeostasis in mice. In humans, plasma BAIBA concentrations are increased with exercise and inversely associated with metabolic risk factors. BAIBA may thus contribute to exercise-induced protection from metabolic diseases. [Copyright &y& Elsevier]
Published: 2014
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44. Cardiorespiratory fitness and brain volume and white matter integrity

Author: Zhu, Na, Jacobs, David R., Schreiner, Pamela J., Launer, Lenore J., Whitmer, Rachel A., Sidney, Stephen, Demerath, Ellen, Thomas, William, Bouchard, Claude, He, Ka, Erus, Guray, Battapady, Harsha, and Bryan, R. Nick
Abstract: We hypothesized that greater cardiorespiratory fitness is associated with lower odds of having unfavorable brain MRI findings.
Published: 2015
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45. Insulin resistance, low cardiorespiratory fitness, and increased exercise blood pressure: contribution of abdominal obesity.

Author: Huot, Maxime, Arsenault, Benoit J., Gaudreault, Valérie, Poirier, Paul, Pérusse, Louis, Tremblay, Angelo, Bouchard, Claude, Despérs, Jean-Pierre, Rhéaume, Caroline, Gaudreault, Valérie, Pérusse, Louis, Després, Jean-Pierre, and Rhéaume, Caroline
Abstract: Individuals with insulin resistance and low cardiorespiratory fitness are frequently found to have an increased waist circumference and high exercise blood pressure. We tested the hypothesis that the relationships among insulin resistance, low cardiorespiratory fitness, and increased exercise blood pressure may be mediated by an elevated waist circumference. This study included 317 apparently healthy men and women (mean age: 34.8±12.8 years; mean body mass index: 26.1±5.2 kg/m(2)). Exercise blood pressure values were measured using a submaximal ergometer test evaluating physical working capacity. Plasma insulin and glucose levels were measured during a 3-hour oral glucose tolerance test. Multivariate regression analyses showed that waist circumference accounted for 32.8% (P<0.0001) and 45.1% (P<0.0001) of the variance in exercise systolic blood pressure in men and women, respectively. Participants were classified into tertiles according to either insulin response, measured during the oral glucose tolerance test, or fitness levels and then further subdivided into 2 subgroups using sex-specific waist circumference thresholds. Individuals with an increased waist circumference (≥94 cm and ≥80 cm for men and women, respectively) had higher exercise systolic blood pressure compared with individuals with low waist circumference, irrespective of their level of insulin resistance (10.6 versus 6.8, 12.2 versus 7.7, and 13.2 versus 8.7 mm Hg/metabolic equivalent, respectively, for the low, intermediate, and high tertiles; P<0.05) or fitness levels (13.1 versus 8.2, 12.0 versus 7.9, and 10.6 versus 7.1 mm Hg/metabolic equivalent, respectively, for the low, intermediate, and high tertiles; P<0.05). Individuals with a higher waist circumference have elevated exercise systolic blood pressure, regardless of their insulin sensitivity or level of cardiorespiratory fitness. [ABSTRACT FROM AUTHOR]
Published: 2011
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46. Overcoming barriers to progress in exercise genomics.

Author: Bouchard C and Bouchard, Claude
Abstract: This commentary focuses on the issues of statistical power, the usefulness of hypothesis-free approaches such as in genome-wide association explorations, the necessity of expanding the research beyond common DNA variants, the advantage of combining transcriptomics with genomics, and the complexities inherent to the search for links between genotype and phenotype in exercise genomics research. [ABSTRACT FROM AUTHOR]
Published: 2011
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47. Overcoming Barriers to Progress in Exercise Genomics.

Author: Bouchard, Claude
Abstract: The article presents information on overcoming the barriers to progress in exercise genomics. It discusses the contribution of genetic factors to phenotypic variation. It also focuses on the identification of genes and deoxyribonucleic acid (DNA) sequence variants and role of human genomic sequence in identifying mendelian disease genes.
Published: 2011
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48. The Association between Short Sleep Duration and Weight Gain Is Dependent on Disinhibited Eating Behavior in Adults.

Author: Chaput, Jean-Philippe, Després, Jean-Pierre, Bouchard, Claude, and Tremblay, Angelo
Published: 2011

49. Association of Single-Nucleotide Polymorphisms From 17 Candidate Genes With Baseline Symptom-Limited Exercise Test Duration and Decrease in Duration Over 20 Years.

Author: Sarzynski, Mark A., Rankinen, Tuomo, Sternfeld, Barbara, Grove, Megan L., Fornage, Myriam, Jacobs Jr, David R., Sidney, Stephen, and Bouchard, Claude
Subjects: CORONARY arteries, DISEASES in young adults, GENETIC polymorphism research, MULTIPLE regression analysis, BIOLOGICAL systems
Abstract: The article provides information on the Coronary Artery Risk Development in Young Adults (CARDIA) fitness study. The test is conducted using general linear model for single-nucleotide polymorphisms (SNPs) with baseline duration and stepwise multiple regression model. It is stated that genotyping of SNPs was performed using the iPLEX MassARRAY genotyping system and Taqman Pre-Validated SNP by Applied Biosystem.
Published: 2010
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50. Fine Mapping of the Insulin-Induced Gene 2 Identifies a Variant Associated With LDL Cholesterol and Total Apolipoprotein B Levels.

Author: Do, Ron, Bailey, Swneke D., Paré, Guillaume, Montpetit, Alexandre, Desbiens, Katia, Hudson, Thomas J., Yusuf, Salim, Bouchard, Claude, Gaudet, Daniel, Pérusse, Louis, Anand, Sonia, Vohl, Marie-Claude, Pastinen, Tomi, and Engert, James C.
Subjects: GENETIC research, BLOOD lipids, APOLIPOPROTEIN E, BLOOD lipoprotein metabolism, LOW density lipoproteins, CHOLESTEROL
Abstract: The article focuses on a study which hypothesized that human insulin-induced gene 2 (INSIG2) variants may have a role in the regulation of plasma lipid and lipoprotein levels. Study authors genotyped 32 single nucleotide polymorphisms (SNPs) in 645 individuals from the Quebec Family Study. They found two SNPs that are associated with plasma low-density lipoprotein cholesterol (LDL-C) and total apolipoprotein B (apoB) levels. Study authors concluded that INSIG2 genetic variants have direct role in lip and lipoprotein metabolism.
Published: 2010
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