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362 results on '"Viikari, JS"'

2. 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

Author

Gorski, M, van der Most, PJ, Teumer, A, Chu, AY, Li, M, Mijatovic, V, Nolte, IM, Cocca, M, Taliun, D, Gomez, F, Li, Y, Tayo, B, Tin, A, Feitosa, MF, Aspelund, T, Attia, J, Biffar, R, Bochud, M, Boerwinkle, E, Borecki, I, Bottinger, EP, Chen, MH, Chouraki, V, Ciullo, M, Coresh, J, Cornelis, MC, Curhan, GC, d'Adamo, AP, Dehghan, A, Dengler, L, Ding, JZ (Jing Zhong), Eiriksdottir, G, Endlich, K, Enroth, S, Esko, T, Franco Duran, OH, Gasparini, P, Gieger, C, Girotto, G, Gottesman, O, Gudnason, V, Gyllensten, U, Hancock, S J, Harris, TB, Helmer, C, Hollerer, S, Hofer, E, Hofman, Bert, Holliday, EG, Homuth, G, Hu, FB, Huth, C, Hutri-Kahonen, N, Hwang, SJ, Imboden, M, Johansson, A, Kahonen, M, Konig, W, Kramer, H, Kramer, BK, Kumar, A, Kutalik, Z, Lambert, JC, Launer, LJ, Lehtimaki, T, Borst, Marja, Navis, G, Swertz, M, Liu, YM, Lohman, K, Loos, RJF, Lu, YC, Lyytikainen, LP, McEvoy, M A, Meisinger, C, Meitinger, T, Metspalu, A, Metzger, M, Mihailov, E, Mitchell, P, Nauck, M, Oldehinkel, AJ, Olden, M, Penninx, B, Pistis, G, Pramstaller, PP, Probst-Hensch, N, Raitakari, OT, Rettig, R, Ridker, PM, Rivadeneira, Fernando, Robino, A, Rosas, SE, Ruderfer, D, Ruggiero, D, Saba, Y, Sala, C, Schmidt, H, Schmidt, R, Scott, RJ, Sedaghat, Sanaz, Smith, AV, Sorice, R, Stengel, B, Stracke, S, Strauch, K, Toniolo, D, Uitterlinden, André, Ulivi, S, Viikari, JS, Volker, U, Vollenweider, P, Volzke, H, Vuckovic, D, Waldenberger, M, Wang, JJ, Yang, QO, Chasman, DI, Tromp, G, Snieder, H, Heid, IM, Fox, CS, Kottgen, A, Pattaro, C, Boger, CA, Fuchsberger, C, Gorski, M, van der Most, PJ, Teumer, A, Chu, AY, Li, M, Mijatovic, V, Nolte, IM, Cocca, M, Taliun, D, Gomez, F, Li, Y, Tayo, B, Tin, A, Feitosa, MF, Aspelund, T, Attia, J, Biffar, R, Bochud, M, Boerwinkle, E, Borecki, I, Bottinger, EP, Chen, MH, Chouraki, V, Ciullo, M, Coresh, J, Cornelis, MC, Curhan, GC, d'Adamo, AP, Dehghan, A, Dengler, L, Ding, JZ (Jing Zhong), Eiriksdottir, G, Endlich, K, Enroth, S, Esko, T, Franco Duran, OH, Gasparini, P, Gieger, C, Girotto, G, Gottesman, O, Gudnason, V, Gyllensten, U, Hancock, S J, Harris, TB, Helmer, C, Hollerer, S, Hofer, E, Hofman, Bert, Holliday, EG, Homuth, G, Hu, FB, Huth, C, Hutri-Kahonen, N, Hwang, SJ, Imboden, M, Johansson, A, Kahonen, M, Konig, W, Kramer, H, Kramer, BK, Kumar, A, Kutalik, Z, Lambert, JC, Launer, LJ, Lehtimaki, T, Borst, Marja, Navis, G, Swertz, M, Liu, YM, Lohman, K, Loos, RJF, Lu, YC, Lyytikainen, LP, McEvoy, M A, Meisinger, C, Meitinger, T, Metspalu, A, Metzger, M, Mihailov, E, Mitchell, P, Nauck, M, Oldehinkel, AJ, Olden, M, Penninx, B, Pistis, G, Pramstaller, PP, Probst-Hensch, N, Raitakari, OT, Rettig, R, Ridker, PM, Rivadeneira, Fernando, Robino, A, Rosas, SE, Ruderfer, D, Ruggiero, D, Saba, Y, Sala, C, Schmidt, H, Schmidt, R, Scott, RJ, Sedaghat, Sanaz, Smith, AV, Sorice, R, Stengel, B, Stracke, S, Strauch, K, Toniolo, D, Uitterlinden, André, Ulivi, S, Viikari, JS, Volker, U, Vollenweider, P, Volzke, H, Vuckovic, D, Waldenberger, M, Wang, JJ, Yang, QO, Chasman, DI, Tromp, G, Snieder, H, Heid, IM, Fox, CS, Kottgen, A, Pattaro, C, Boger, CA, and Fuchsberger, C

Published
2017

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

Author

Kilpelainen, TO, Carli, J F M, Skowronski, A A, Sun, Q, Kriebel, J, Feitosa, MF, Hedman, AK, Drong, AW, Hayes, J E, Zhao, JH, Pers, TH, Schick, U, Grarup, N, Kutalik, Z, Trompet, S, Mangino, M, Kristiansson, K, Beekman, M, Lyytikainen, LP, Eriksson, J, Henneman, Peter, Lahti, J, Tanaka, T, Luan, JA, Del Greco, F, Pasko, D, Renstrom, F, Willems, SM, Mahajan, A, Rose, LM, Guo, XQ, Liu, YM, Kleber, ME, Perusse, L, Gaunt, T, Ahluwalia, TS, Sung, YJ, Ramos, YF, Amin, Najaf, Amuzu, A, Barroso, I, Bellis, C, Blangero, J, Buckley, BM, Bohringer, S, Chen, YDI, de Craen, A J N, Crosslin, DR, Dale, CE, Dastani, Z, Day, FR, Deelen, J, Delgado, GE, Demirkan, Ayse, Finucane, FM, Ford, I, Garcia, ME, Gieger, C, Gustafsson, S, Hallmans, G, Hankinson, SE, Havulinna, AS, Herder, Cindy, Hernandez, D, Hicks, AA, Hunter, DJ, Illig, T, Ingelsson, E, Ioan-Facsinay, A, Jansson, JO, Jenny, NS, Jorgensen, ME, Jorgensen, T, Karlsson, M, Koenig, W, Kraft, P, Kwekkeboom, J, Laatikainen, T, Ladwig, KH, LeDuc, C A, Lowe, G, Lu, YC, Marques-Vidal, P, Meisinger, C, Menni, C, Morris, AP, Myers, RH, Mannisto, S, Nalls, MA, Paternoster, L, Peters, A, Pradhan, A D, Rankinen, T, Rasmussen-Torvik, LJ, Rathmann, W, Rice, TK, Richards, JB, Ridker, PM, Sattar, N, Savage, DB, Soderberg, S, Timpson, NJ, Vandenput, L, van Heemst, D, Uh, HW, Vohl, MC, Walker, M, Wichmann, HE, Widen, E, Wood, AR, Yao, J, Zeller, T, Zhang, YY, Meulenbelt, I, Kloppenburg, M, Astrup, A, Sorensen, TIA, Sarzynski, MA, Rao, DC, Jousilahti, P, Vartiainen, E, Hofman, Bert, Rivadeneira, Fernando, Uitterlinden, André, Kajantie, E, Osmond, C, Palotie, A, Eriksson, JG, Heliovaara, M, Knekt, PB, Koskinen, S, Jula, A, Perola, M, Huupponen, R K, Viikari, JS, Kahonen, M, Lehtimaki, T, Raitakari, OT, Mellstrom, D, Lorentzon, M, Casas, JP, Bandinelli, S, Marz, W, Isaacs, Aaron, van Dijk, KW, Duijn, Cornelia, Harris, TB, Bouchard, C, Allison, MA, Chasman, DI, Ohlsson, C, Lind, L, Scott, RA, Langenberg, C, Wareham, NJ, Ferrucci, L, Frayling, TM, Pramstaller, PP, Borecki, IB, Waterworth, DM, Bergmann, S, Waeber, G, Vollenweider, P, Vestergaard, H, Hansen, T, Pedersen, O, Hu, FB, Slagboom, PE (Eline), Grallert, H, Spector, TD, Jukema, JW, Klein, RJ, Schadt, EE, Franks, PW, Lindgren, CM, Leibel, R L, Loos, RJF, Kilpelainen, TO, Carli, J F M, Skowronski, A A, Sun, Q, Kriebel, J, Feitosa, MF, Hedman, AK, Drong, AW, Hayes, J E, Zhao, JH, Pers, TH, Schick, U, Grarup, N, Kutalik, Z, Trompet, S, Mangino, M, Kristiansson, K, Beekman, M, Lyytikainen, LP, Eriksson, J, Henneman, Peter, Lahti, J, Tanaka, T, Luan, JA, Del Greco, F, Pasko, D, Renstrom, F, Willems, SM, Mahajan, A, Rose, LM, Guo, XQ, Liu, YM, Kleber, ME, Perusse, L, Gaunt, T, Ahluwalia, TS, Sung, YJ, Ramos, YF, Amin, Najaf, Amuzu, A, Barroso, I, Bellis, C, Blangero, J, Buckley, BM, Bohringer, S, Chen, YDI, de Craen, A J N, Crosslin, DR, Dale, CE, Dastani, Z, Day, FR, Deelen, J, Delgado, GE, Demirkan, Ayse, Finucane, FM, Ford, I, Garcia, ME, Gieger, C, Gustafsson, S, Hallmans, G, Hankinson, SE, Havulinna, AS, Herder, Cindy, Hernandez, D, Hicks, AA, Hunter, DJ, Illig, T, Ingelsson, E, Ioan-Facsinay, A, Jansson, JO, Jenny, NS, Jorgensen, ME, Jorgensen, T, Karlsson, M, Koenig, W, Kraft, P, Kwekkeboom, J, Laatikainen, T, Ladwig, KH, LeDuc, C A, Lowe, G, Lu, YC, Marques-Vidal, P, Meisinger, C, Menni, C, Morris, AP, Myers, RH, Mannisto, S, Nalls, MA, Paternoster, L, Peters, A, Pradhan, A D, Rankinen, T, Rasmussen-Torvik, LJ, Rathmann, W, Rice, TK, Richards, JB, Ridker, PM, Sattar, N, Savage, DB, Soderberg, S, Timpson, NJ, Vandenput, L, van Heemst, D, Uh, HW, Vohl, MC, Walker, M, Wichmann, HE, Widen, E, Wood, AR, Yao, J, Zeller, T, Zhang, YY, Meulenbelt, I, Kloppenburg, M, Astrup, A, Sorensen, TIA, Sarzynski, MA, Rao, DC, Jousilahti, P, Vartiainen, E, Hofman, Bert, Rivadeneira, Fernando, Uitterlinden, André, Kajantie, E, Osmond, C, Palotie, A, Eriksson, JG, Heliovaara, M, Knekt, PB, Koskinen, S, Jula, A, Perola, M, Huupponen, R K, Viikari, JS, Kahonen, M, Lehtimaki, T, Raitakari, OT, Mellstrom, D, Lorentzon, M, Casas, JP, Bandinelli, S, Marz, W, Isaacs, Aaron, van Dijk, KW, Duijn, Cornelia, Harris, TB, Bouchard, C, Allison, MA, Chasman, DI, Ohlsson, C, Lind, L, Scott, RA, Langenberg, C, Wareham, NJ, Ferrucci, L, Frayling, TM, Pramstaller, PP, Borecki, IB, Waterworth, DM, Bergmann, S, Waeber, G, Vollenweider, P, Vestergaard, H, Hansen, T, Pedersen, O, Hu, FB, Slagboom, PE (Eline), Grallert, H, Spector, TD, Jukema, JW, Klein, RJ, Schadt, EE, Franks, PW, Lindgren, CM, Leibel, R L, and Loos, RJF

Published
2016

4. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Author

Ried, JS, Jeff, JM, Chu, AY, Bragg-Gresham, JL, Dongen, J, Huffman, JE, Ahluwalia, TS, Cadby, G, Eklund, N, Eriksson, J, Esko, T, Feitosa, MF, Goel, A, Gorski, M, Hayward, C, Heard-Costa, NL, Jackson, AU, Jokinen, E, Kanoni, S, Kristiansson, K, Kutalik, Z, Lahti, J, Luan, JA, Magi, R, Mahajan, A, Mangino, M, Medina-Gomez, C, Monda, KL, Nolte, IM (Ilja), Perusse, L, Prokopenko, I, Qi, L, Rose, LM, Salvi, E, Smith, M T, Snieder, H, Stancakova, A, Sung, YJ, Tachmazidou, I, Teumer, A, Thorleifsson, G, van der Harst, P, Walker, RW, Wang, SR, Wild, SH, Willems, SM, Wong, A, Zhang, WH, Albrecht, E, Alves, AC, Bakker, SJL, Barlassina, C, Bartz, TM, Beilby, J, Bellis, C, Bergman, RN, Bergmann, S, Blangero, J, Bluher, M, Boerwinkle, E, Bonnycastle, LL, Bornstein, SR, Bruinenberg, M, Campbell, H, Chen, YDI, Chiang, CWK, Chines, PS, Collins, FS, Cucca, F, Cupples, LA, D'Avila, F, de Geus, EJC, Dedoussis, G, Dimitriou, M, Doring, A, Eriksson, JG, Farmaki, AE, Farrall, M, Ferreira, T, Fischer, K (Kirsten), Forouhi, NG, Friedrich, N, Gjesing, AP, Glorioso, N, Graff, M, Grallert, H, Grarup, N, Grassler, J, Grewal, J, Hamsten, A, Harder, MN, Hartman, CA, Hassinen, M, Hastie, N, Hattersley, AT, Havulinna, AS, Heliovaara, M, Hillege, H, Hofman, Bert, Holmen, O, Homuth, G, Hottenga, JJ (Jouke Jan), Hui, JN, Husemoen, LL, Hysi, PG, Isaacs, Aaron, Ittermann, T, Jalilzadeh, S, James, AL, Jorgensen, T, Jousilahti, P, Jula, A, Justesen, JM, Justice, AE, Kahonen, M, Karaleftheri, M, Khaw, KT, Keinanen-Kiukaanniemi, SM, Kinnunen, L, Knekt, PB, Koistinen, HA, Kolcic, I, Kooner, IK, Koskinen, S, Kovacs, P, Kyriakou, T, Laitinen, T, Langenberg, C, Lewin, AM, Lichtner, P, Lindgren, CM, Lindstrom, J, Linneberg, A, Lorbeer, R, Lorentzon, M, Luben, R, Lyssenko, V, Mannisto, S, Manunta, P, Leach, IM, McArdle, WL, McKnight, B, Mohlke, KL, Mihailov, E, Milani, L, Mills, R, Montasser, ME, Morris, AP, Muller, G, Musk, AW, Narisu, N, Ong, KK, Oostra, B, Osmond, C, Palotie, A, Pankow, JS, Paternoster, L, Penninx, BW, Pichler, I, Pilia, MG, Polasek, O, Pramstaller, PP, Raitakari, OT, Rankinen, T, Rao, DC, Rayner, NW, Ribel-Madsen, R, Rice, TK, Richards, M, Ridker, PM, Rivadeneira, Fernando, Ryan, KA, Sanna, S, Sarzynski, MA, Scholtens, s, Scott, RA, Sebert, S, Southam, L, Sparso, TH, Steinthorsdottir, V, Stirrups, K, Stolk, RP (Ronald), Strauch, K, Stringham, HM, Swertz, MA, Swift, AJ, Tonjes, A, Tsafantakis, E, van der Most, PJ, van Vliet-Ostaptchouk, JV, Vandenput, L, Vartiainen, E, Venturini, C, Verweij, N (Niek), Viikari, JS, Vitart, V, Vohl, MC, Vonk, JM, Waeber, G, Widen, E, Willemsen, G, Wilsgaard, T, Winkler, TW, Wright, AF, Yerges-Armstrong, LM, Zhao, JH, Zillikens, M.C., Boomsma, DI, Bouchard, C, Chambers, JC, Chasman, DI, Cusi, D, Gansevoort, RT, Gieger, C, Hansen, T, Hicks, AA, Hu, F, Hveem, K, Jarvelin, MR, Kajantie, E, Kooner, JS, Kuh, D, Kuusisto, J, Laakso, M, Lakka, TA, Lehtimaki, T, Metspalu, A, Njolstad, I, Ohlsson, C, Oldehinkel, AJ (A.), Palmer, LJ, Pedersen, O, Perola, M, Peters, A, Psaty, BM, Puolijoki, H, Rauramaa, R, Rudan, I, Salomaa, V, Schwarz, PEH, Shudiner, A R, Smit, JH, Sorensen, TIA, Spector, TD, Stefansson, K, Stumvoll, M, Tremblay, A, Tuomilehto, J, Uitterlinden, André, Uusitupa, M, Volker, U, Vollenweider, P, Wareham, NJ, Watkins, H, Wilson, JF, Zeggini, E, Abecasis, GR, Boehnke, M, Borecki, IB, Deloukas, P, Duijn, Cornelia, Fox, C, Groop, LC, Heid, IM, Hunter, DJ, Kaplan, RC, McCarthy, MI, North, KE, O'Connell, JR, Schlessinger, D, Thorsteinsdottir, U, Strachan, DP, Frayling, T, Hirschhorn, JN, Muller-Nurasyid, M, Loos, RJF, Ried, JS, Jeff, JM, Chu, AY, Bragg-Gresham, JL, Dongen, J, Huffman, JE, Ahluwalia, TS, Cadby, G, Eklund, N, Eriksson, J, Esko, T, Feitosa, MF, Goel, A, Gorski, M, Hayward, C, Heard-Costa, NL, Jackson, AU, Jokinen, E, Kanoni, S, Kristiansson, K, Kutalik, Z, Lahti, J, Luan, JA, Magi, R, Mahajan, A, Mangino, M, Medina-Gomez, C, Monda, KL, Nolte, IM (Ilja), Perusse, L, Prokopenko, I, Qi, L, Rose, LM, Salvi, E, Smith, M T, Snieder, H, Stancakova, A, Sung, YJ, Tachmazidou, I, Teumer, A, Thorleifsson, G, van der Harst, P, Walker, RW, Wang, SR, Wild, SH, Willems, SM, Wong, A, Zhang, WH, Albrecht, E, Alves, AC, Bakker, SJL, Barlassina, C, Bartz, TM, Beilby, J, Bellis, C, Bergman, RN, Bergmann, S, Blangero, J, Bluher, M, Boerwinkle, E, Bonnycastle, LL, Bornstein, SR, Bruinenberg, M, Campbell, H, Chen, YDI, Chiang, CWK, Chines, PS, Collins, FS, Cucca, F, Cupples, LA, D'Avila, F, de Geus, EJC, Dedoussis, G, Dimitriou, M, Doring, A, Eriksson, JG, Farmaki, AE, Farrall, M, Ferreira, T, Fischer, K (Kirsten), Forouhi, NG, Friedrich, N, Gjesing, AP, Glorioso, N, Graff, M, Grallert, H, Grarup, N, Grassler, J, Grewal, J, Hamsten, A, Harder, MN, Hartman, CA, Hassinen, M, Hastie, N, Hattersley, AT, Havulinna, AS, Heliovaara, M, Hillege, H, Hofman, Bert, Holmen, O, Homuth, G, Hottenga, JJ (Jouke Jan), Hui, JN, Husemoen, LL, Hysi, PG, Isaacs, Aaron, Ittermann, T, Jalilzadeh, S, James, AL, Jorgensen, T, Jousilahti, P, Jula, A, Justesen, JM, Justice, AE, Kahonen, M, Karaleftheri, M, Khaw, KT, Keinanen-Kiukaanniemi, SM, Kinnunen, L, Knekt, PB, Koistinen, HA, Kolcic, I, Kooner, IK, Koskinen, S, Kovacs, P, Kyriakou, T, Laitinen, T, Langenberg, C, Lewin, AM, Lichtner, P, Lindgren, CM, Lindstrom, J, Linneberg, A, Lorbeer, R, Lorentzon, M, Luben, R, Lyssenko, V, Mannisto, S, Manunta, P, Leach, IM, McArdle, WL, McKnight, B, Mohlke, KL, Mihailov, E, Milani, L, Mills, R, Montasser, ME, Morris, AP, Muller, G, Musk, AW, Narisu, N, Ong, KK, Oostra, B, Osmond, C, Palotie, A, Pankow, JS, Paternoster, L, Penninx, BW, Pichler, I, Pilia, MG, Polasek, O, Pramstaller, PP, Raitakari, OT, Rankinen, T, Rao, DC, Rayner, NW, Ribel-Madsen, R, Rice, TK, Richards, M, Ridker, PM, Rivadeneira, Fernando, Ryan, KA, Sanna, S, Sarzynski, MA, Scholtens, s, Scott, RA, Sebert, S, Southam, L, Sparso, TH, Steinthorsdottir, V, Stirrups, K, Stolk, RP (Ronald), Strauch, K, Stringham, HM, Swertz, MA, Swift, AJ, Tonjes, A, Tsafantakis, E, van der Most, PJ, van Vliet-Ostaptchouk, JV, Vandenput, L, Vartiainen, E, Venturini, C, Verweij, N (Niek), Viikari, JS, Vitart, V, Vohl, MC, Vonk, JM, Waeber, G, Widen, E, Willemsen, G, Wilsgaard, T, Winkler, TW, Wright, AF, Yerges-Armstrong, LM, Zhao, JH, Zillikens, M.C., Boomsma, DI, Bouchard, C, Chambers, JC, Chasman, DI, Cusi, D, Gansevoort, RT, Gieger, C, Hansen, T, Hicks, AA, Hu, F, Hveem, K, Jarvelin, MR, Kajantie, E, Kooner, JS, Kuh, D, Kuusisto, J, Laakso, M, Lakka, TA, Lehtimaki, T, Metspalu, A, Njolstad, I, Ohlsson, C, Oldehinkel, AJ (A.), Palmer, LJ, Pedersen, O, Perola, M, Peters, A, Psaty, BM, Puolijoki, H, Rauramaa, R, Rudan, I, Salomaa, V, Schwarz, PEH, Shudiner, A R, Smit, JH, Sorensen, TIA, Spector, TD, Stefansson, K, Stumvoll, M, Tremblay, A, Tuomilehto, J, Uitterlinden, André, Uusitupa, M, Volker, U, Vollenweider, P, Wareham, NJ, Watkins, H, Wilson, JF, Zeggini, E, Abecasis, GR, Boehnke, M, Borecki, IB, Deloukas, P, Duijn, Cornelia, Fox, C, Groop, LC, Heid, IM, Hunter, DJ, Kaplan, RC, McCarthy, MI, North, KE, O'Connell, JR, Schlessinger, D, Thorsteinsdottir, U, Strachan, DP, Frayling, T, Hirschhorn, JN, Muller-Nurasyid, M, and Loos, RJF

Published
2016

5. y New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk

Author

Lu, YC, Day, FR, Gustafsson, S, Buchkovich, ML, Na, JB, Bataille, V, Cousminer, DL, Dastani, Z, Drong, AW, Esko, T, Evans, DM, Falchi, M, Feitosa, MF, Ferreira, T, Hedman, AK, Haring, R, Hysi, PG, Iles, MM, Justice, AE, Kanoni, S, Lagou, V, Li, R, Li, X, Locke, A, Lu, C, Magi, R, Perry, JRB, Pers, TH, Qi, QB, Sanna, M, Schmidt, EM, Scott, WR, Shungin, D, Teumer, A, Vinkhuyzen, AAE, Walker, RW, Westra, HJ, Zhang, MF, Zhang, WH, Zhao, JH, Zhu, ZH, Afzal, U, Ahluwalia, TS, Bakker, SJL, Bellis, C, Bonnefond, A, Borodulin, K, Buchman, AS, Cederholm, T, Choh, AC, Choi, HJ, Curran, JE, de Groot, LCPGM (Lisette), De Jager, PL, Dhonukshe-Rutten, RAM, Enneman, Anke, Eury, E, Evans, DS, Forsen, T, Friedrich, N, Fumeron, F, Garcia, ME, Gartner, S, Han, BG, Havulinna, AS, Hayward, C, Hernandez, D, Hillege, H, Ittermann, T, Kent, JW, Kolcic, I, Laatikainen, T, Lahti, J, Leach, IM, Lee, CG, Lee, JY, Liu, T, Liu, YF, Lobbens, S, Loh, M, Lyytikainen, LP, Medina-Gomez, C, Michaelsson, K, Nalls, MA, Nielson, CM, Oozageer, L, Pascoe, L, Paternoster, L, Polasek, O, Ripatti, S, Sarzynski, MA, Shin, CS, Narancic, NS, Spira, D, Srikanth, P, Steinhagen-Thiessen, E, Sung, YJ, Swart, KMA, Taittonen, L, Tanaka, T, Tikkanen, E, van der Velde, Nathalie, Schoor, NM, Verweij, N (Niek), Wright, AF, Yu, L, Zmuda, JM, Eklund, N, Forrester, T, Grarup, N, Jackson, AU, Kristiansson, K, Kuulasmaa, T, Kuusisto, J, Lichtner, P, Luan, JA, Mahajan, A, Mannisto, S, Palmer, CD, Ried, JS, Scott, RA, Stancakova, A, Wagner, PJ, Demirkan, Ayse, Doring, A, Gudnason, V, Kiel, DP, Kuhnel, B, Mangino, M, McKnight, B, Menni, C, O'Connell, JR, Oostra, Ben, Shuldiner, AR, Song, KJ, Vandenput, L, Duijn, Cornelia, Vollenweider, P, White, CC, Boehnke, M, Boettcher, Y, Cooper, RS, Forouhi, NG, Gieger, C, Grallert, H, Hingorani, A, Jorgensen, T, Jousilahti, P, Kivimaki, M, Kumari, M, Laakso, M, Langenberg, C, Linneberg, A, Luke, A, McKenzie, CA, Palotie, A, Pedersen, O, Peters, A, Strauch, K, Tayo, BO, Wareham, NJ, Bennett, DA, Bertram, L, Blangero, J, Bluher, M, Bouchard, C, Campbell, H, Cho, NH, Cummings, SR, Czerwinski, SA, Demuth, I, Eckardt, R, Eriksson, JG, Ferrucci, L, Franco Duran, OH, Froguel, P, Gansevoort, RT, Hansen, T, Harris, TB, Hastie, N, Heliovaara, M, Hofman, Bert, Jordan, JM, Jula, A, Kahonen, M, Kajantie, E, Knekt, PB, Koskinen, S, Kovacs, P, Lehtimaki, T, Lind, L, Liu, YM, Orwoll, ES, Osmond, C, Perola, M, Perusse, L, Raitakari, OT, Rankinen, T, Rao, DC, Rice, TK, Rivadeneira, Fernando, Rudan, I, Salomaa, V, Sorensen, TIA, Stumvoll, M, Tonjes, A, Towne, B, Tranah, GJ, Tremblay, A, Uitterlinden, André, van der Harst, P, Vartiainen, E, Viikari, JS, Vitart, V, Vohl, MC, Volzke, H, Walker, M, Wallaschofski, H, Wild, S, Wilson, JF, Yengo, L, Bishop, DT, Borecki, IB, Chambers, JC, Cupples, LA, Dehghan, Abbas, Deloukas, P, Fatemifar, G, Fox, C, Furey, TS, Franke, L, Han, JL, Hunter, DJ, Karjalainen, J, Karpe, F, Kaplan, RC, Kooner, JS, McCarthy, MI, Murabito, JM, Morris, AP, Bishop, JAN, North, KE, Ohlsson, C, Ong, KK, Prokopenko, I, Richards, JB, Schadt, EE, Spector, TD, Widen, E, Willer, CJ, Yang, Jiaqi, Ingelsson, E, Mohlke, KL, Hirschhorn, JN, Pospisilik, JA, Zillikens, M.C., Lindgren, C, Kilpelainen, TO, Loos, RJF, Lu, YC, Day, FR, Gustafsson, S, Buchkovich, ML, Na, JB, Bataille, V, Cousminer, DL, Dastani, Z, Drong, AW, Esko, T, Evans, DM, Falchi, M, Feitosa, MF, Ferreira, T, Hedman, AK, Haring, R, Hysi, PG, Iles, MM, Justice, AE, Kanoni, S, Lagou, V, Li, R, Li, X, Locke, A, Lu, C, Magi, R, Perry, JRB, Pers, TH, Qi, QB, Sanna, M, Schmidt, EM, Scott, WR, Shungin, D, Teumer, A, Vinkhuyzen, AAE, Walker, RW, Westra, HJ, Zhang, MF, Zhang, WH, Zhao, JH, Zhu, ZH, Afzal, U, Ahluwalia, TS, Bakker, SJL, Bellis, C, Bonnefond, A, Borodulin, K, Buchman, AS, Cederholm, T, Choh, AC, Choi, HJ, Curran, JE, de Groot, LCPGM (Lisette), De Jager, PL, Dhonukshe-Rutten, RAM, Enneman, Anke, Eury, E, Evans, DS, Forsen, T, Friedrich, N, Fumeron, F, Garcia, ME, Gartner, S, Han, BG, Havulinna, AS, Hayward, C, Hernandez, D, Hillege, H, Ittermann, T, Kent, JW, Kolcic, I, Laatikainen, T, Lahti, J, Leach, IM, Lee, CG, Lee, JY, Liu, T, Liu, YF, Lobbens, S, Loh, M, Lyytikainen, LP, Medina-Gomez, C, Michaelsson, K, Nalls, MA, Nielson, CM, Oozageer, L, Pascoe, L, Paternoster, L, Polasek, O, Ripatti, S, Sarzynski, MA, Shin, CS, Narancic, NS, Spira, D, Srikanth, P, Steinhagen-Thiessen, E, Sung, YJ, Swart, KMA, Taittonen, L, Tanaka, T, Tikkanen, E, van der Velde, Nathalie, Schoor, NM, Verweij, N (Niek), Wright, AF, Yu, L, Zmuda, JM, Eklund, N, Forrester, T, Grarup, N, Jackson, AU, Kristiansson, K, Kuulasmaa, T, Kuusisto, J, Lichtner, P, Luan, JA, Mahajan, A, Mannisto, S, Palmer, CD, Ried, JS, Scott, RA, Stancakova, A, Wagner, PJ, Demirkan, Ayse, Doring, A, Gudnason, V, Kiel, DP, Kuhnel, B, Mangino, M, McKnight, B, Menni, C, O'Connell, JR, Oostra, Ben, Shuldiner, AR, Song, KJ, Vandenput, L, Duijn, Cornelia, Vollenweider, P, White, CC, Boehnke, M, Boettcher, Y, Cooper, RS, Forouhi, NG, Gieger, C, Grallert, H, Hingorani, A, Jorgensen, T, Jousilahti, P, Kivimaki, M, Kumari, M, Laakso, M, Langenberg, C, Linneberg, A, Luke, A, McKenzie, CA, Palotie, A, Pedersen, O, Peters, A, Strauch, K, Tayo, BO, Wareham, NJ, Bennett, DA, Bertram, L, Blangero, J, Bluher, M, Bouchard, C, Campbell, H, Cho, NH, Cummings, SR, Czerwinski, SA, Demuth, I, Eckardt, R, Eriksson, JG, Ferrucci, L, Franco Duran, OH, Froguel, P, Gansevoort, RT, Hansen, T, Harris, TB, Hastie, N, Heliovaara, M, Hofman, Bert, Jordan, JM, Jula, A, Kahonen, M, Kajantie, E, Knekt, PB, Koskinen, S, Kovacs, P, Lehtimaki, T, Lind, L, Liu, YM, Orwoll, ES, Osmond, C, Perola, M, Perusse, L, Raitakari, OT, Rankinen, T, Rao, DC, Rice, TK, Rivadeneira, Fernando, Rudan, I, Salomaa, V, Sorensen, TIA, Stumvoll, M, Tonjes, A, Towne, B, Tranah, GJ, Tremblay, A, Uitterlinden, André, van der Harst, P, Vartiainen, E, Viikari, JS, Vitart, V, Vohl, MC, Volzke, H, Walker, M, Wallaschofski, H, Wild, S, Wilson, JF, Yengo, L, Bishop, DT, Borecki, IB, Chambers, JC, Cupples, LA, Dehghan, Abbas, Deloukas, P, Fatemifar, G, Fox, C, Furey, TS, Franke, L, Han, JL, Hunter, DJ, Karjalainen, J, Karpe, F, Kaplan, RC, Kooner, JS, McCarthy, MI, Murabito, JM, Morris, AP, Bishop, JAN, North, KE, Ohlsson, C, Ong, KK, Prokopenko, I, Richards, JB, Schadt, EE, Spector, TD, Widen, E, Willer, CJ, Yang, Jiaqi, Ingelsson, E, Mohlke, KL, Hirschhorn, JN, Pospisilik, JA, Zillikens, M.C., Lindgren, C, Kilpelainen, TO, and Loos, RJF

Abstract

To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P < 5 x 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.

Published
2016

6. Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Author

Leeuwen, Elisa, Sabo, A, Bis, JC, Huffman, JE, Manichaikul, A, Smith, AV, Feitosa, MF, Demissie, S, Joshi, PK, Duan, Q, Marten, J, van Klinken, JB, Surakka, I, Nolte, IM, Zhang, WH, Mbarek, H, Li-Gao, RF, Trompet, S, Verweij, N, Evangelou, E, Lyytikainen, LP, Tayo, BO, Deelen, J, van der Most, PJ, van der Laan, SW, Arking, DE, Morrison, A, Dehghan, Abbas, Franco Duran, OH, Hofman, Bert, Rivadeneira, Fernando, Sijbrands, E.J.G., Uitterlinden, André, Mychaleckyj, JC, Campbell, A (Archie), Hocking, LJ, Padmanabhan, S, Brody, JA, Rice, KM, White, CC, Harris, T, Isaacs, Aaron, Campbell, H, Lange, LA, Rudan, I, Kolcic, I, Navarro, P, Zemunik, T, Salomaa, V, Kooner, AS, Kooner, JS, Lehne, B, Scott, WR, Tan, ST, de Geus, EJ, Milaneschi, Y, Penninx, BWJH, Willemsen, G, de Mutsert, R, Ford, I, Gansevoort, RT, Segura-Lepe, M P, Raitakari, OT, Viikari, JS, Nikus, K, Forrester, T, McKenzie, CA, de Craen, AJM, den Ruijter, HM, Pasterkamp, G, Snieder, H, Oldehinkel, AJ, Slagboom, PE (Eline), Cooper, RS, Kahonen, M, Lehtimaki, T, Elliott, P, van der Harst, P, Jukema, JW, Mook-Kanamori, DO, Boomsma, DI, Chambers, JC, Swertz, M, Ripatti, S, van Dijk, KW, Vitart, V, Polasek, O, Hayward, C, Wilson, JG, Wilson, JF, Gudnason, V, Rich, SS, Psaty, BM, Borecki, IB, Boerwinkle, E, Rotter, JI, Cupples, LA, Duijn, Cornelia, Leeuwen, Elisa, Sabo, A, Bis, JC, Huffman, JE, Manichaikul, A, Smith, AV, Feitosa, MF, Demissie, S, Joshi, PK, Duan, Q, Marten, J, van Klinken, JB, Surakka, I, Nolte, IM, Zhang, WH, Mbarek, H, Li-Gao, RF, Trompet, S, Verweij, N, Evangelou, E, Lyytikainen, LP, Tayo, BO, Deelen, J, van der Most, PJ, van der Laan, SW, Arking, DE, Morrison, A, Dehghan, Abbas, Franco Duran, OH, Hofman, Bert, Rivadeneira, Fernando, Sijbrands, E.J.G., Uitterlinden, André, Mychaleckyj, JC, Campbell, A (Archie), Hocking, LJ, Padmanabhan, S, Brody, JA, Rice, KM, White, CC, Harris, T, Isaacs, Aaron, Campbell, H, Lange, LA, Rudan, I, Kolcic, I, Navarro, P, Zemunik, T, Salomaa, V, Kooner, AS, Kooner, JS, Lehne, B, Scott, WR, Tan, ST, de Geus, EJ, Milaneschi, Y, Penninx, BWJH, Willemsen, G, de Mutsert, R, Ford, I, Gansevoort, RT, Segura-Lepe, M P, Raitakari, OT, Viikari, JS, Nikus, K, Forrester, T, McKenzie, CA, de Craen, AJM, den Ruijter, HM, Pasterkamp, G, Snieder, H, Oldehinkel, AJ, Slagboom, PE (Eline), Cooper, RS, Kahonen, M, Lehtimaki, T, Elliott, P, van der Harst, P, Jukema, JW, Mook-Kanamori, DO, Boomsma, DI, Chambers, JC, Swertz, M, Ripatti, S, van Dijk, KW, Vitart, V, Polasek, O, Hayward, C, Wilson, JG, Wilson, JF, Gudnason, V, Rich, SS, Psaty, BM, Borecki, IB, Boerwinkle, E, Rotter, JI, Cupples, LA, and Duijn, Cornelia

Published
2016

7. Genome-wide association study identifies 17 new loci influencing concentrations of circulating cytokines and growth factors

Author

Ahola-Olli, AV, primary, Würtz, P, additional, Havulinna, AS, additional, Aalto, K, additional, Pitkänen, N, additional, Lehtimäki, T, additional, Kähönen, M, additional, Lyytikäinen, LP, additional, Raitoharju, E, additional, Seppälä, I, additional, Sarin, AP, additional, Ripatti, S, additional, Palotie, A, additional, Perola, M, additional, Viikari, JS, additional, Jalkanen, S, additional, Maksimow, M, additional, Salomaa, V, additional, Salmi, M, additional, Kettunen, J, additional, and Raitakari, OT, additional

Published
2016
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8. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

Author

Winkler, TW, Justice, AE, Graff, M, Barata, L, Feitosa, MF, Chu, S, Czajkowski, J, Esko, T, Fall, T, Kilpelainen, TO, Lu, YC, Magi, R, Mihailov, E, Pers, TH, Rueger, S, Teumer, A, Ehret, GB, Ferreira, T, Heard-Costa, NL, Karjalainen, J, Lagou, V, Mahajan, A, Neinast, MD, Prokopenko, I, Simino, J, Teslovich, TM, Jansen, R, Westra, HJ, White, CC, Absher, D, Ahluwalia, TS, Ahmad, Shahzad, Albrecht, E, Alves, AC, Bragg-Gresham, JL, de Craen, AJM, Bis, JC, Bonnefond, A, Boucher, G, Cadby, G, Cheng, YC, Chiang, CWK, Delgado, G, Demirkan, Ayse, Dueker, N, Eklund, N, Eiriksdottir, G, Eriksson, J, Feenstra, B, Fischer, K (Kirsten), Frau, F, Galesloot, TE, Geller, F, Goel, A, Gorski, M, Grammer, TB, Gustafsson, S, Haitjema, S, Hottenga, JJ (Jouke Jan), Huffman, JE, Jackson, AU, Jacobs, KB, Johansson, A, Kaakinen, M, Kleber, ME, Lahti, J, Leach, IM, Lehne, B, Liu, YF, Lo, KS, Lorentzon, M, Luan, J, Madden, PAF, Mangino, M, McKnight, B, Medina Gomez, Maria, Monda, KL, Montasser, ME, Muller, G, Muller-Nurasyid, M, Nolte, IM (Ilja), Panoutsopoulou, K, Pascoe, L, Paternoster, L, Rayner, NW, Renstrom, F, Rizzi, F, Rose, LM, Ryan, KA, Salo, P, Sanna, S, Scharnagl, H, Shi, JX, Smith, AV, Southam, L, Stancakova, A, Steinthorsdottir, V, Strawbridge, RJ, Sung, YJ, Tachmazidou, I, Tanaka, T, Thorleifsson, G, Trompet, S, Pervjakova, N, Tyrer, JP, Vandenput, L, Laan, Sander, van der Velde, Nathalie, van Setten, J, van Vliet-Ostaptchouk, JV, Verweij, N (Niek), Vlachopoulou, E, Waite, LL, Wang, SR, Wang, ZM, Wild, SH, Willenborg, C, Wilson, JF, Wong, A, Yang, Jiaqi, Yengo, L, Yerges-Armstrong, LM, Yu, L, Zhang, WH, Zhao, JH, Andersson, EA, Bakker, SJL, Baldassarre, D, Banasik, K, Barcella, M, Barlassina, C, Bellis, C, Benaglio, P, Blangero, J, Bluher, M, Bonnet, F, Bonnycastle, LL, Boyd, HA, Bruinenberg, M, Buchman, AS, Campbell, H, Chen, YDI, Chines, PS, Claudi-Boehm, S, Cole, J, Collins, FS, de Geus, EJC, de Groot, LCPGM (Lisette), Dimitriou, M, Duan, J, Enroth, S, Eury, E, Farmaki, AE, Forouhi, NG, Friedrich, N, Gejman, PV, Gigante, B, Glorioso, N, Go, AS, Gottesman, O, Grassler, J, Grallert, H, Grarup, N, Gu, YM, Broer, Linda, Ham, Annelies, Hansen, T, Harris, TB, Hartman, CA, Hassinen, M, Hastie, N, Hattersley, AT, Heath, AC, Henders, AK, Hernandez, D, Hillege, H, Holmen, O, Hovingh, KG, Hui, J, Husemoen, LL, Hutri-Kahonen, N, Hysi, PG, Illig, T, De Jager, PL, Jalilzadeh, S, Jorgensen, T, Jukema, JW, Juonala, M, Kanoni, S, Karaleftheri, M, Khaw, KT, Kinnunen, L, Kittner, SJ, Koenig, W, Kolcic, I, Kovacs, P, Krarup, NT, Kratzer, W, Kruger, J, Kuh, D, Kumari, M, Kyriakou, T, Langenberg, C, Lannfelt, L, Lanzani, C, Lotay, V, Launer, LJ (Lenore), Leander, K, Lindstrom, J, Linneberg, A, Liu, YP, Lobbens, S, Luben, R, Lyssenko, V, Mannisto, S, Magnusson, PK, McArdle, WL, Menni, C, Merger, S, Milani, L, Montgomery, GW, Morris, AP, Narisu, N, Nelis, M, Ong, KK, Palotie, A, Perusse, L, Pichler, I, Pilia, MG, Pouta, A, Rheinberger, M, Ribel-Madsen, R, Richards, M, Rice, KM, Rice, TK, Rivolta, C, Salomaa, V, Sanders, AR, Sarzynski, MA, Scholtens, s, Scott, RA, Scott, WR, Sebert, S, Sengupta, S, Sennblad, B, Seufferlein, T, Silveira, A, Slagboom, PE (Eline), Smit, JH, Sparso, TH, Stirrups, K, Stolk, RP (Ronald), Stringham, HM, Swertz, MA, Swift, AJ, Syvanen, AC, Tan, ST, Thorand, B, Tonjes, A, Tremblay, A, Tsafantakis, E, van der Most, PJ, Volker, U, Vohl, MC, Vonk, JM, Waldenberger, M, Walker, RW, Wennauer, R, Widen, E, Willemsen, G, Wilsgaard, T, Wright, AF, Zillikens, M.C., Boon - van Dijk, Suzanne, Schoor, NM, Asselbergs, FW, de Bakker, PIW, Beckmann, JS, Beilby, J, Bennett, DA, Bergman, RN, Bergmann, S, Boger, CA, Boehm, BO, Boerwinkle, E, Boomsma, DI, Bornstein, SR, Bottinger, EP, Bouchard, C, Chambers, JC, Chanock, SJ, Chasman, DI, Cucca, F, Cusi, D, Dedoussis, G, Erdmann, J, Eriksson, JG, Evans, DA, de Faire, U, Farrall, M, Ferrucci, L, Ford, I, Franke, L, Franks, PW, Froguel, P, Gansevoort, RT, Gieger, C, Gronberg, H, Gudnason, V, Gyllensten, U, Hall, P, Hamsten, A, van der Harst, P, Hayward, C, Heliovaara, M, Hengstenberg, C, Hicks, AA, Hingorani, A, Hofman, Bert, Hu, F, Huikuri, HV, Hveem, K, James, AL, Jordan, JM, Jula, A, Kahonen, M, Kajantie, E, Kathiresan, S, Kiemeney, LALM, Kivimaki, M, Knekt, PB, Koistinen, HA, Kooner, JS, Koskinen, S, Kuusisto, J, Maerz, W, Martin, NG, Laakso, M, Lakka, TA, Lehtimaki, T, Lettre, G, Levinson, DF, Lind, L, Lokki, ML, Mantyselka, P, Melbye, M, Metspalu, A, Mitchell, BD, Moll, FL, Murray, JC, Musk, AW, Nieminen, MS, Njolstad, I, Ohlsson, C, Oldehinkel, AJ (A.), Oostra, Ben, Palmer, LJ, Pankow, JS, Pasterkamp, G, Pedersen, NL, Pedersen, O, Penninx, BW, Perola, M, Peters, A, Polasek, O, Pramstaller, PP, Psaty, BM, Qi, L, Quertermous, T, Raitakari, OT, Rankinen, T, Rauramaa, R, Ridker, PM, Rioux, JD, Rivadeneira, Fernando, Rotter, JI, Rudan, I, den Ruijter, HM, Saltevo, J, Sattar, N, Schunkert, H, Schwarz, PEH, Shuldiner, AR, Sinisalo, J, Snieder, H, Sorensen, TIA, Spector, TD, Staessen, JA, Stefania, B, Thorsteinsdottir, U, Stumvoll, M, Tardif, JC, Tremoli, E, Tuomilehto, J, Uitterlinden, André, Uusitupa, M, Verbeek, ALM, Vermeulen, SH, Viikari, JS, Vitart, V, Volzke, H, Vollenweider, P, Waeber, G, Walker, M, Wallaschofski, H, Wareham, NJ, Watkins, H, Zeggini, E, Chakravarti, A, Clegg, DJ, Cupples, LA, Gordon-Larsen, P, Jaquish, CE, Rao, DC, Abecasis, GR, Assimes, TL, Barroso, I, Berndt, SI, Boehnke, M, Deloukas, P, Fox, CS, Groop, LC, Hunter, DJ, Ingelsson, E, Kaplan, RC, McCarthy, MI, Mohlke, KL, O'Connell, JR, Schlessinger, D, Strachan, DP, Stefansson, K, Duijn, Cornelia, Hirschhorn, JN, Lindgren, CM, Heid, IM, North, KE, Borecki, IB, Kutalik, Z, Loos, RJF, Winkler, TW, Justice, AE, Graff, M, Barata, L, Feitosa, MF, Chu, S, Czajkowski, J, Esko, T, Fall, T, Kilpelainen, TO, Lu, YC, Magi, R, Mihailov, E, Pers, TH, Rueger, S, Teumer, A, Ehret, GB, Ferreira, T, Heard-Costa, NL, Karjalainen, J, Lagou, V, Mahajan, A, Neinast, MD, Prokopenko, I, Simino, J, Teslovich, TM, Jansen, R, Westra, HJ, White, CC, Absher, D, Ahluwalia, TS, Ahmad, Shahzad, Albrecht, E, Alves, AC, Bragg-Gresham, JL, de Craen, AJM, Bis, JC, Bonnefond, A, Boucher, G, Cadby, G, Cheng, YC, Chiang, CWK, Delgado, G, Demirkan, Ayse, Dueker, N, Eklund, N, Eiriksdottir, G, Eriksson, J, Feenstra, B, Fischer, K (Kirsten), Frau, F, Galesloot, TE, Geller, F, Goel, A, Gorski, M, Grammer, TB, Gustafsson, S, Haitjema, S, Hottenga, JJ (Jouke Jan), Huffman, JE, Jackson, AU, Jacobs, KB, Johansson, A, Kaakinen, M, Kleber, ME, Lahti, J, Leach, IM, Lehne, B, Liu, YF, Lo, KS, Lorentzon, M, Luan, J, Madden, PAF, Mangino, M, McKnight, B, Medina Gomez, Maria, Monda, KL, Montasser, ME, Muller, G, Muller-Nurasyid, M, Nolte, IM (Ilja), Panoutsopoulou, K, Pascoe, L, Paternoster, L, Rayner, NW, Renstrom, F, Rizzi, F, Rose, LM, Ryan, KA, Salo, P, Sanna, S, Scharnagl, H, Shi, JX, Smith, AV, Southam, L, Stancakova, A, Steinthorsdottir, V, Strawbridge, RJ, Sung, YJ, Tachmazidou, I, Tanaka, T, Thorleifsson, G, Trompet, S, Pervjakova, N, Tyrer, JP, Vandenput, L, Laan, Sander, van der Velde, Nathalie, van Setten, J, van Vliet-Ostaptchouk, JV, Verweij, N (Niek), Vlachopoulou, E, Waite, LL, Wang, SR, Wang, ZM, Wild, SH, Willenborg, C, Wilson, JF, Wong, A, Yang, Jiaqi, Yengo, L, Yerges-Armstrong, LM, Yu, L, Zhang, WH, Zhao, JH, Andersson, EA, Bakker, SJL, Baldassarre, D, Banasik, K, Barcella, M, Barlassina, C, Bellis, C, Benaglio, P, Blangero, J, Bluher, M, Bonnet, F, Bonnycastle, LL, Boyd, HA, Bruinenberg, M, Buchman, AS, Campbell, H, Chen, YDI, Chines, PS, Claudi-Boehm, S, Cole, J, Collins, FS, de Geus, EJC, de Groot, LCPGM (Lisette), Dimitriou, M, Duan, J, Enroth, S, Eury, E, Farmaki, AE, Forouhi, NG, Friedrich, N, Gejman, PV, Gigante, B, Glorioso, N, Go, AS, Gottesman, O, Grassler, J, Grallert, H, Grarup, N, Gu, YM, Broer, Linda, Ham, Annelies, Hansen, T, Harris, TB, Hartman, CA, Hassinen, M, Hastie, N, Hattersley, AT, Heath, AC, Henders, AK, Hernandez, D, Hillege, H, Holmen, O, Hovingh, KG, Hui, J, Husemoen, LL, Hutri-Kahonen, N, Hysi, PG, Illig, T, De Jager, PL, Jalilzadeh, S, Jorgensen, T, Jukema, JW, Juonala, M, Kanoni, S, Karaleftheri, M, Khaw, KT, Kinnunen, L, Kittner, SJ, Koenig, W, Kolcic, I, Kovacs, P, Krarup, NT, Kratzer, W, Kruger, J, Kuh, D, Kumari, M, Kyriakou, T, Langenberg, C, Lannfelt, L, Lanzani, C, Lotay, V, Launer, LJ (Lenore), Leander, K, Lindstrom, J, Linneberg, A, Liu, YP, Lobbens, S, Luben, R, Lyssenko, V, Mannisto, S, Magnusson, PK, McArdle, WL, Menni, C, Merger, S, Milani, L, Montgomery, GW, Morris, AP, Narisu, N, Nelis, M, Ong, KK, Palotie, A, Perusse, L, Pichler, I, Pilia, MG, Pouta, A, Rheinberger, M, Ribel-Madsen, R, Richards, M, Rice, KM, Rice, TK, Rivolta, C, Salomaa, V, Sanders, AR, Sarzynski, MA, Scholtens, s, Scott, RA, Scott, WR, Sebert, S, Sengupta, S, Sennblad, B, Seufferlein, T, Silveira, A, Slagboom, PE (Eline), Smit, JH, Sparso, TH, Stirrups, K, Stolk, RP (Ronald), Stringham, HM, Swertz, MA, Swift, AJ, Syvanen, AC, Tan, ST, Thorand, B, Tonjes, A, Tremblay, A, Tsafantakis, E, van der Most, PJ, Volker, U, Vohl, MC, Vonk, JM, Waldenberger, M, Walker, RW, Wennauer, R, Widen, E, Willemsen, G, Wilsgaard, T, Wright, AF, Zillikens, M.C., Boon - van Dijk, Suzanne, Schoor, NM, Asselbergs, FW, de Bakker, PIW, Beckmann, JS, Beilby, J, Bennett, DA, Bergman, RN, Bergmann, S, Boger, CA, Boehm, BO, Boerwinkle, E, Boomsma, DI, Bornstein, SR, Bottinger, EP, Bouchard, C, Chambers, JC, Chanock, SJ, Chasman, DI, Cucca, F, Cusi, D, Dedoussis, G, Erdmann, J, Eriksson, JG, Evans, DA, de Faire, U, Farrall, M, Ferrucci, L, Ford, I, Franke, L, Franks, PW, Froguel, P, Gansevoort, RT, Gieger, C, Gronberg, H, Gudnason, V, Gyllensten, U, Hall, P, Hamsten, A, van der Harst, P, Hayward, C, Heliovaara, M, Hengstenberg, C, Hicks, AA, Hingorani, A, Hofman, Bert, Hu, F, Huikuri, HV, Hveem, K, James, AL, Jordan, JM, Jula, A, Kahonen, M, Kajantie, E, Kathiresan, S, Kiemeney, LALM, Kivimaki, M, Knekt, PB, Koistinen, HA, Kooner, JS, Koskinen, S, Kuusisto, J, Maerz, W, Martin, NG, Laakso, M, Lakka, TA, Lehtimaki, T, Lettre, G, Levinson, DF, Lind, L, Lokki, ML, Mantyselka, P, Melbye, M, Metspalu, A, Mitchell, BD, Moll, FL, Murray, JC, Musk, AW, Nieminen, MS, Njolstad, I, Ohlsson, C, Oldehinkel, AJ (A.), Oostra, Ben, Palmer, LJ, Pankow, JS, Pasterkamp, G, Pedersen, NL, Pedersen, O, Penninx, BW, Perola, M, Peters, A, Polasek, O, Pramstaller, PP, Psaty, BM, Qi, L, Quertermous, T, Raitakari, OT, Rankinen, T, Rauramaa, R, Ridker, PM, Rioux, JD, Rivadeneira, Fernando, Rotter, JI, Rudan, I, den Ruijter, HM, Saltevo, J, Sattar, N, Schunkert, H, Schwarz, PEH, Shuldiner, AR, Sinisalo, J, Snieder, H, Sorensen, TIA, Spector, TD, Staessen, JA, Stefania, B, Thorsteinsdottir, U, Stumvoll, M, Tardif, JC, Tremoli, E, Tuomilehto, J, Uitterlinden, André, Uusitupa, M, Verbeek, ALM, Vermeulen, SH, Viikari, JS, Vitart, V, Volzke, H, Vollenweider, P, Waeber, G, Walker, M, Wallaschofski, H, Wareham, NJ, Watkins, H, Zeggini, E, Chakravarti, A, Clegg, DJ, Cupples, LA, Gordon-Larsen, P, Jaquish, CE, Rao, DC, Abecasis, GR, Assimes, TL, Barroso, I, Berndt, SI, Boehnke, M, Deloukas, P, Fox, CS, Groop, LC, Hunter, DJ, Ingelsson, E, Kaplan, RC, McCarthy, MI, Mohlke, KL, O'Connell, JR, Schlessinger, D, Strachan, DP, Stefansson, K, Duijn, Cornelia, Hirschhorn, JN, Lindgren, CM, Heid, IM, North, KE, Borecki, IB, Kutalik, Z, and Loos, RJF

Abstract

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age-and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to similar to 2.8M SNPs with BMI and WHRadjBMI in four strata (men <= 50y, men > 50y, women <= 50y, women > 50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR< 5%) age-specific effects, of which 11 had larger effects in younger (< 50y) than in older adults (>= 50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may providefurther insights into the biology that underlies weight change with age or the sexually dimorphism of body shap

Published
2015

9. Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

Author

Horikoshi, M, Magi, R, van de Bunt, M, Surakka, I, Sarin, AP, Mahajan, A, Marullo, L, Thorleifsson, G, Hagg, S, Hottenga, JJ (Jouke Jan), Ladenvall, C, Ried, JS, Winkler, TW, Willems, SM, Pervjakova, N, Esko, T, Beekman, M, Nelson, CP, Willenborg, C, Wiltshire, S, Ferreira, T, Fernandez, J, Gaulton, KJ, Steinthorsdottir, V, Hamsten, A, Magnusson, PKE, Willemsen, G, Milaneschi, Y, Robertson, NR, Groves, CJ, Bennett, AJ, Lehtimaki, T, Viikari, JS, Rung, J, Lyssenko, V, Perola, M, Heid, IM, Herder, Cindy, Grallert, H, Muller-Nurasyid, M, Roden, M, Hypponen, E, Isaacs, Aaron, Leeuwen, Elisa, Karssen, Lennart, Mihailov, E, Houwing-Duistermaat, JJ, de Craen, AJM, Deelen, J, Havulinna, AS, Blades, M, Hengstenberg, C, Erdmann, J, Schunkert, H, Kaprio, J, Tobin, MD, Samani, NJ, Lind, L, Salomaa, V, Lindgren, CM, Slagboom, PE (Eline), Metspalu, A, Duijn, Cornelia, Eriksson, JG, Peters, A, Gieger, C, Jula, A, Groop, L, Raitakari, OT, Power, C, Penninx, BWJH, de Geus, ED, Smit, JH, Boomsma, DI, Pedersen, NL, Ingelsson, E, Thorsteinsdottir, U, Stefansson, K, Ripatti, S, Prokopenko, I, McCarthy, MI, Morris, AP, Horikoshi, M, Magi, R, van de Bunt, M, Surakka, I, Sarin, AP, Mahajan, A, Marullo, L, Thorleifsson, G, Hagg, S, Hottenga, JJ (Jouke Jan), Ladenvall, C, Ried, JS, Winkler, TW, Willems, SM, Pervjakova, N, Esko, T, Beekman, M, Nelson, CP, Willenborg, C, Wiltshire, S, Ferreira, T, Fernandez, J, Gaulton, KJ, Steinthorsdottir, V, Hamsten, A, Magnusson, PKE, Willemsen, G, Milaneschi, Y, Robertson, NR, Groves, CJ, Bennett, AJ, Lehtimaki, T, Viikari, JS, Rung, J, Lyssenko, V, Perola, M, Heid, IM, Herder, Cindy, Grallert, H, Muller-Nurasyid, M, Roden, M, Hypponen, E, Isaacs, Aaron, Leeuwen, Elisa, Karssen, Lennart, Mihailov, E, Houwing-Duistermaat, JJ, de Craen, AJM, Deelen, J, Havulinna, AS, Blades, M, Hengstenberg, C, Erdmann, J, Schunkert, H, Kaprio, J, Tobin, MD, Samani, NJ, Lind, L, Salomaa, V, Lindgren, CM, Slagboom, PE (Eline), Metspalu, A, Duijn, Cornelia, Eriksson, JG, Peters, A, Gieger, C, Jula, A, Groop, L, Raitakari, OT, Power, C, Penninx, BWJH, de Geus, ED, Smit, JH, Boomsma, DI, Pedersen, NL, Ingelsson, E, Thorsteinsdottir, U, Stefansson, K, Ripatti, S, Prokopenko, I, McCarthy, MI, and Morris, AP

Abstract

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency >= 0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Published
2015

10. Early growth genetics C. New loci associated with birgh weight identify genetic links between intrauterine growth and adult height and metabolism

Author

Horikoshi, M, Yaghootkar, H, Mook, Dennis, Sovio, U, Taal, Rob, Hennig, BJ, Bradfield, JP, St Pourcain, B, Evans, DM, Charoen, P, Kaakinen, M, Cousminer, DL, Lehtimaki, T, Kreiner-Moller, E, Warrington, NM, Bustamante, M, Feenstra, B, Berry, DJ, Thiering, E, Pfab, T, Barton, SJ, Shields, BM, Kerkhof, M, Leeuwen, Elisa, Fulford, AJ, Kutalik, Z, Zhao, JH, den Hoed, M, Mahajan, A, Lindi, V, Goh, LK, Hottenga, JJ (Jouke Jan), Wu, Fenny, Raitakari, OT, Harder, M, Meirhaeghe, A, Ntalla, I, Salem, RM, Jameson, KA, Zhou, K, Monies, D, Lagou, V, Kirin, M, Heikkinen, J, Adair, LS, Alkuraya, FS, Al-Odaib, A, Amouyel, P, Andersson, EAS, Bennett, AJ, Blakemore, AIF, Buxton, JL, Dallongeville, J, Das, Suman, de Geus, EJC, Estivill, X, Flexeder, C, Froguel, P, Geller, F, Godfrey, KM, Gottrand, F, Groves, CJ, Hansen, T, Hirschhorn, JN, Hofman, Bert, Hollegaard, MV, Hougaard, DM, Hypponen, E, Inskip, H, Isaacs, Aaron, Jorgensen, T, Kanaka-Gentenbein, C, Kemp, JP, Kiess, W, Kipelainen, TO, Klopp, N, Knight, BA, Kuzawa, CW, McMahon, G, Newnham, JP, Niinikoski, H, Oostra, Ben, Pedersen, L, Postma, DS, Ring, SM, Rivadeneira, Fernando, Robertson, NR, Sebert, S, Simell, O, Slowinski, T, Tiesler, CMT, Tonjes, A, Vaag, A, Viikari, JS, Vink, JM, Vissing, NH, Wareham, NJ, Willemsen, G, Witte, DR, Zhang, H, Zhao, J, Wilson, JF, Stumvoll, M, Prentice, AM, Meyer, BF, Pearson, ER, Boreham, CA, Cooper, C, Gilman, MW, Dedoussis, GV, Moreno, LA, Pedersen, O, Saarinen, M, Mohlke, KL, Boomsma, DI, Saw, SM, Lakka, TA, Korner, A, Loos, RJ, Ong, KK, Vollenweider, P, Duijn, Cornelia, Koppelman, GH, Hattersley, AT, Holloway, JW, Hocher, B, Heinrich, J, Power, C, Melbye, M, Guxens Junyent, Monica, Pennell, CE, Bonnelykke, K, Bisgaard, H, Eriksson, JG, Widen, E, Hakonarson, H, Uitterlinden, André, Pouta, A, Lawlor, DA, Smith, GD, Frayling, TM, McCarthy, M, Grant, SFA, Jaddoe, Vincent, Jarvelin, MR, Timpson, NJ, Prokopenko, I, Freathy, RM, Erasmus MC other, Epidemiology, Medical Microbiology & Infectious Diseases, Clinical Genetics, Internal Medicine, and Hematology

Published
2013

11. Selenium Status and Blood Lipids: The Cardiovascular Risk in Young Finns Study

Author

Stranges, S, Tabák, AG, Guallar, E, Rayman, MP, Akbaraly, TN, Laclaustra, M, Alfthan, G, Mussalo-Rauhamaa, H, Viikari, JS, Raitakari, OT, and Kivimäki, M

Subjects
Male, Adolescent, Cholesterol, HDL, Cholesterol, LDL, Article, Selenium, Cross-Sectional Studies, Cardiovascular Diseases, Risk Factors, Child, Preschool, Humans, Female, Child, Finland, Triglycerides, Follow-Up Studies
Abstract

Stranges S, Tabák AG, Guallar E, Rayman MP, Akbaraly TN, Laclaustra M, Alfthan G, Mussalo-Rauhamaa H, Viikari JSA, Raitakari OT, Kivimäki M (Health Sciences Research Institute, University of Warwick Medical School, Coventry; University College London, London, UK; Semmelweis University Faculty of Medicine, Budapest, Hungary; Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; National Center for Cardiovascular Research (CNIC), Madrid, Spain; University of Surrey, UK; National Institute of Health and Medical Research (Inserm) U888. F-34000 Montpellier, France; National Institute for Health and Welfare, Helsinki, Finland; Hjelt Institute, University of Helsinki, Helsinki; University of Turku and Turku University Hospital, Turku; University of Turku, Turku; Finnish Institute of Occupational Health and University of Helsinki, Helsinki, Finland). Selenium status and blood lipids: the cardiovascular risk in young finns study. J Intern Med 2011; doi: 10.1111/j.1365-2796.2011.02398.x. Background. Concern has been recently raised about possible adverse cardio-metabolic effects of high selenium status, such as increased risks of diabetes and hyperlipidaemia. However, most of the evidence comes from selenium-replete populations such as that of the United States. Objectives. To examine cross-sectional and longitudinal associations of serum selenium with cardiovascular risk factors in Finland where selenium levels were amongst the lowest in the world until the early 1980s before the implementation of a nationwide selenium fertilization programme. Methods. Serum selenium was measured in 1235 young Finns aged 3-18 years at baseline in 1980 (prefertilization) and in a subgroup (N = 262) at the 6-year follow-up (1986, postfertilization). During the 27-year follow-up, serum lipids, blood pressure, body mass index and smoking were assessed five times (1980, 1983, 1986, 2001 and 2007). Results. Mean (±SD) serum selenium concentrations were 74.3 ± 14.0 ng mL(-1) in 1980 and 106.6 ± 12.5 ng mL(-1) in 1986 (average increase 32.3 ng mL(-1) ; 95% CI: 30.3 to 34.3, P

Published
2011

12. Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization

Author

Arking, D, Pulit, S, Crotti, L, van der Harst, P, Munroe, P, Koopmann, T, Sotoodehnia, N, Rossin, E, Morley, M, Wang, X, Johnson, A, Lundby, A, Gudbjartsson, D, Noseworthy, P, Eijgelsheim, M, Bradford, Y, Tarasov, K, Dörr, M, Müller-Nurasyid, M, Lahtinen, A, Nolte, I, Smith, A, Bis, J, Isaacs, A, Newhouse, S, Evans, D, Post, W, Waggott, D, Lyytikäinen, L, Hicks, A, Eisele, L, Ellinghaus, D, Hayward, C, Navarro, P, Ulivi, S, Tanaka, T, Tester, D, Chatel, S, Gustafsson, S, Kumari, M, Morris, R, Naluai, A, Padmanabhan, S, Kluttig, A, Strohmer, B, Panayiotou, A, Torres, M, Knoflach, M, Hubacek, J, Slowikowski, K, Raychaudhuri, S, Kumar, R, Harris, T, Launer, L, Shuldiner, A, Alonso, A, Bader, J, Ehret, G, Huang, H, Kao, W, Strait, J, Macfarlane, P, Brown, M, Caulfield, M, Samani, N, Kronenberg, F, Willeit, J, Smith, J, Greiser, K, Meyer Zu Schwabedissen, H, Werdan, K, Carella, M, Zelante, L, Heckbert, S, Psaty, B, Rotter, J, Kolcic, I, Polašek, O, Wright, A, Griffin, M, Daly, M, Arnar, D, Hólm, H, Thorsteinsdottir, U, Denny, J, Roden, D, Zuvich, R, Emilsson, V, Plump, A, Larson, M, O'Donnell, C, Yin, X, Bobbo, M, D'Adamo, A, Iorio, A, Sinagra, G, Carracedo, A, Cummings, S, Nalls, M, Jula, A, Kontula, K, Marjamaa, A, Oikarinen, L, Perola, M, Porthan, K, Erbel, R, Hoffmann, P, Jöckel, K, Kälsch, H, Nöthen, M, den Hoed, M, Loos, R, Thelle, D, Gieger, C, Meitinger, T, Perz, S, Peters, A, Prucha, H, Sinner, M, Waldenberger, M, de Boer, R, Franke, L, van der Vleuten, P, Beckmann, B, Martens, E, Bardai, A, Hofman, N, Wilde, A, Behr, E, Dalageorgou, C, Giudicessi, J, Medeiros-Domingo, A, Kyndt, F, Probst, V, Ghidoni, A, Insolia, R, Hamilton, R, Scherer, S, Brandimarto, J, Margulies, K, Moravec, C, Greco, M, Fuchsberger, C, O'Connell, J, Lee, W, Watt, G, Campbell, H, Wild, S, El Mokhtari, N, Frey, N, Asselbergs, F, Mateo Leach, I, Navis, G, van den Berg, M, van Veldhuisen, D, Kellis, M, Krijthe, B, Franco, O, Hofman, A, Kors, J, Uitterlinden, A, Witteman, J, Kedenko, L, Lamina, C, Oostra, B, Abecasis, G, Lakatta, E, Mulas, A, Orrú, M, Schlessinger, D, Uda, M, Markus, M, Völker, U, Snieder, H, Spector, T, Arnlöv, J, Lind, L, Sundström, J, Syvänen, A, Kivimaki, M, Kähönen, M, Mononen, N, Raitakari, O, Viikari, J, Adamkova, V, Kiechl, S, Brion, M, Nicolaides, A, Paulweber, B, Haerting, J, Dominiczak, A, Nyberg, F, Whincup, P, Hingorani, A, Schott, J, Bezzina, C, Ingelsson, E, Ferrucci, L, Gasparini, P, Wilson, J, Rudan, I, Franke, A, Mühleisen, T, Pramstaller, P, Lehtimäki, T, Paterson, A, Parsa, A, Liu, Y, van Duijn, C, Siscovick, D, Gudnason, V, Jamshidi, Y, Salomaa, V, Felix, S, Sanna, S, Ritchie, M, Stricker, B, Stefansson, K, Boyer, L, Cappola, T, Olsen, J, Lage, K, Schwartz, P, Kääb, S, Chakravarti, A, Ackerman, M, Pfeufer, A, de Bakker, P, Newton-Cheh, C, Arking, DE, Pulit, SL, Munroe, PB, Rossin, EJ, Johnson, AD, Gudbjartsson, DF, Noseworthy, PA, Tarasov, KV, Lahtinen, AM, Nolte, IM, Smith, AV, Bis, JC, Newhouse, SJ, Evans, DS, Post, WS, Lyytikäinen, LP, Hicks, AA, Tester, DJ, Morris, RW, Naluai, AT, Panayiotou, AG, Hubacek, JA, Kumar, RD, Harris, TB, Launer, LJ, Shuldiner, AR, Bader, JS, Kao, WH, Strait, JB, Macfarlane, PW, Caulfield, MJ, Samani, NJ, Smith, JG, Greiser, KH, Heckbert, SR, Psaty, BM, Rotter, JI, Wright, AF, Daly, MJ, Arnar, DO, Denny, JC, Roden, DM, Zuvich, RL, Plump, AS, Larson, MG, O'Donnell, CJ, D'Adamo, AP, Cummings, SR, Nalls, MA, Kontula, KK, Jöckel, KH, Nöthen, MM, Loos, RJ, Thelle, DS, Sinner, MF, de Boer, RA, van der Vleuten, PA, Beckmann, BM, Wilde, AA, Behr, ER, Giudicessi, JR, Hamilton, RM, Scherer, SW, Moravec, CE, Greco, MFD, O'Connell, JR, Lee, WK, Watt, GC, Wild, SH, El Mokhtari, NE, Asselbergs, FW, van den Berg, MP, van Veldhuisen, DJ, Krijthe, BP, Franco, OH, Kors, JA, Uitterlinden, AG, Witteman, JC, Oostra, BA, Abecasis, GR, Lakatta, EG, Markus, MR, Spector, TD, Syvänen, AC, Raitakari, OT, Viikari, JS, Nicolaides, AN, Dominiczak, AF, Whincup, PH, Hingorani, AD, Schott, JJ, Bezzina, CR, Wilson, JF, Mühleisen, TW, Pramstaller, PP, Lehtimäki, TJ, Paterson, AD, van Duijn, CM, Siscovick, DS, Felix, SB, Ritchie, MD, Stricker, BH, Boyer, LA, Cappola, TP, Olsen, JV, Schwartz, PJ, Ackerman, MJ, de Bakker, PI, Arking, D, Pulit, S, Crotti, L, van der Harst, P, Munroe, P, Koopmann, T, Sotoodehnia, N, Rossin, E, Morley, M, Wang, X, Johnson, A, Lundby, A, Gudbjartsson, D, Noseworthy, P, Eijgelsheim, M, Bradford, Y, Tarasov, K, Dörr, M, Müller-Nurasyid, M, Lahtinen, A, Nolte, I, Smith, A, Bis, J, Isaacs, A, Newhouse, S, Evans, D, Post, W, Waggott, D, Lyytikäinen, L, Hicks, A, Eisele, L, Ellinghaus, D, Hayward, C, Navarro, P, Ulivi, S, Tanaka, T, Tester, D, Chatel, S, Gustafsson, S, Kumari, M, Morris, R, Naluai, A, Padmanabhan, S, Kluttig, A, Strohmer, B, Panayiotou, A, Torres, M, Knoflach, M, Hubacek, J, Slowikowski, K, Raychaudhuri, S, Kumar, R, Harris, T, Launer, L, Shuldiner, A, Alonso, A, Bader, J, Ehret, G, Huang, H, Kao, W, Strait, J, Macfarlane, P, Brown, M, Caulfield, M, Samani, N, Kronenberg, F, Willeit, J, Smith, J, Greiser, K, Meyer Zu Schwabedissen, H, Werdan, K, Carella, M, Zelante, L, Heckbert, S, Psaty, B, Rotter, J, Kolcic, I, Polašek, O, Wright, A, Griffin, M, Daly, M, Arnar, D, Hólm, H, Thorsteinsdottir, U, Denny, J, Roden, D, Zuvich, R, Emilsson, V, Plump, A, Larson, M, O'Donnell, C, Yin, X, Bobbo, M, D'Adamo, A, Iorio, A, Sinagra, G, Carracedo, A, Cummings, S, Nalls, M, Jula, A, Kontula, K, Marjamaa, A, Oikarinen, L, Perola, M, Porthan, K, Erbel, R, Hoffmann, P, Jöckel, K, Kälsch, H, Nöthen, M, den Hoed, M, Loos, R, Thelle, D, Gieger, C, Meitinger, T, Perz, S, Peters, A, Prucha, H, Sinner, M, Waldenberger, M, de Boer, R, Franke, L, van der Vleuten, P, Beckmann, B, Martens, E, Bardai, A, Hofman, N, Wilde, A, Behr, E, Dalageorgou, C, Giudicessi, J, Medeiros-Domingo, A, Kyndt, F, Probst, V, Ghidoni, A, Insolia, R, Hamilton, R, Scherer, S, Brandimarto, J, Margulies, K, Moravec, C, Greco, M, Fuchsberger, C, O'Connell, J, Lee, W, Watt, G, Campbell, H, Wild, S, El Mokhtari, N, Frey, N, Asselbergs, F, Mateo Leach, I, Navis, G, van den Berg, M, van Veldhuisen, D, Kellis, M, Krijthe, B, Franco, O, Hofman, A, Kors, J, Uitterlinden, A, Witteman, J, Kedenko, L, Lamina, C, Oostra, B, Abecasis, G, Lakatta, E, Mulas, A, Orrú, M, Schlessinger, D, Uda, M, Markus, M, Völker, U, Snieder, H, Spector, T, Arnlöv, J, Lind, L, Sundström, J, Syvänen, A, Kivimaki, M, Kähönen, M, Mononen, N, Raitakari, O, Viikari, J, Adamkova, V, Kiechl, S, Brion, M, Nicolaides, A, Paulweber, B, Haerting, J, Dominiczak, A, Nyberg, F, Whincup, P, Hingorani, A, Schott, J, Bezzina, C, Ingelsson, E, Ferrucci, L, Gasparini, P, Wilson, J, Rudan, I, Franke, A, Mühleisen, T, Pramstaller, P, Lehtimäki, T, Paterson, A, Parsa, A, Liu, Y, van Duijn, C, Siscovick, D, Gudnason, V, Jamshidi, Y, Salomaa, V, Felix, S, Sanna, S, Ritchie, M, Stricker, B, Stefansson, K, Boyer, L, Cappola, T, Olsen, J, Lage, K, Schwartz, P, Kääb, S, Chakravarti, A, Ackerman, M, Pfeufer, A, de Bakker, P, Newton-Cheh, C, Arking, DE, Pulit, SL, Munroe, PB, Rossin, EJ, Johnson, AD, Gudbjartsson, DF, Noseworthy, PA, Tarasov, KV, Lahtinen, AM, Nolte, IM, Smith, AV, Bis, JC, Newhouse, SJ, Evans, DS, Post, WS, Lyytikäinen, LP, Hicks, AA, Tester, DJ, Morris, RW, Naluai, AT, Panayiotou, AG, Hubacek, JA, Kumar, RD, Harris, TB, Launer, LJ, Shuldiner, AR, Bader, JS, Kao, WH, Strait, JB, Macfarlane, PW, Caulfield, MJ, Samani, NJ, Smith, JG, Greiser, KH, Heckbert, SR, Psaty, BM, Rotter, JI, Wright, AF, Daly, MJ, Arnar, DO, Denny, JC, Roden, DM, Zuvich, RL, Plump, AS, Larson, MG, O'Donnell, CJ, D'Adamo, AP, Cummings, SR, Nalls, MA, Kontula, KK, Jöckel, KH, Nöthen, MM, Loos, RJ, Thelle, DS, Sinner, MF, de Boer, RA, van der Vleuten, PA, Beckmann, BM, Wilde, AA, Behr, ER, Giudicessi, JR, Hamilton, RM, Scherer, SW, Moravec, CE, Greco, MFD, O'Connell, JR, Lee, WK, Watt, GC, Wild, SH, El Mokhtari, NE, Asselbergs, FW, van den Berg, MP, van Veldhuisen, DJ, Krijthe, BP, Franco, OH, Kors, JA, Uitterlinden, AG, Witteman, JC, Oostra, BA, Abecasis, GR, Lakatta, EG, Markus, MR, Spector, TD, Syvänen, AC, Raitakari, OT, Viikari, JS, Nicolaides, AN, Dominiczak, AF, Whincup, PH, Hingorani, AD, Schott, JJ, Bezzina, CR, Wilson, JF, Mühleisen, TW, Pramstaller, PP, Lehtimäki, TJ, Paterson, AD, van Duijn, CM, Siscovick, DS, Felix, SB, Ritchie, MD, Stricker, BH, Boyer, LA, Cappola, TP, Olsen, JV, Schwartz, PJ, Ackerman, MJ, and de Bakker, PI

Abstract

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Published
2014

13. A Genome-Wide Screen for Interactions Reveals a New Locus on 4p15 Modifying the Effect of Waist-to-Hip Ratio on Total Cholesterol

Author

Surakka, I, Isaacs, Aaron, Karssen, Lennart, Laurila, PPP, Middelberg, RPS, Tikkanen, E, Ried, JS, Lamina, C, Mangino, M, Igl, W, Hottenga, JJ (Jouke Jan), Lagou, V, van der Harst, P, Leach, IM, Esko, T, Kutalik, Z, Wainwright, NW, Struchalin, Maksim, Sarin, AP, Kangas, AJ, Viikari, JS, Perola, M, Rantanen, T, Petersen, AK, Soininen, P, Johansson, A, Soranzo, N, Heath, AC, Papamarkou, T, Prokopenko, I, Tonjes, A, Kronenberg, F, Doring, A, Rivadeneira, Fernando, Montgomery, GW, Whitfield, JB, Kahonen, M, Lehtimaki, T, Freimer, NB, Willemsen, G, de Geus, EJC, Palotie, A, Sandhu, MS, Waterworth, DM, Metspalu, A, Stumvoll, M, Uitterlinden, André, Jula, A, Navis, G, Wijmenga, C, Wolffenbuttel, BHR, Taskinen, MR, Ala-Korpela, M, Kaprio, J, Kyvik, KO, Boomsma, DI, Pedersen, NL, Gyllensten, U, Wilson, JF, Rudan, I, Campbell, H, Pramstaller, PP, Spector, TD, Witteman, JCM, Eriksson, JG, Salomaa, V, Oostra, Ben, Raitakari, OT, Wichmann, HE, Gieger, C, Jarvelin, MR, Martin, NG, Hofman, Bert, McCarthy, MI, Peltonen, L, Duijn, Cornelia, Aulchenko, YS, Ripatti, S, Surakka, I, Isaacs, Aaron, Karssen, Lennart, Laurila, PPP, Middelberg, RPS, Tikkanen, E, Ried, JS, Lamina, C, Mangino, M, Igl, W, Hottenga, JJ (Jouke Jan), Lagou, V, van der Harst, P, Leach, IM, Esko, T, Kutalik, Z, Wainwright, NW, Struchalin, Maksim, Sarin, AP, Kangas, AJ, Viikari, JS, Perola, M, Rantanen, T, Petersen, AK, Soininen, P, Johansson, A, Soranzo, N, Heath, AC, Papamarkou, T, Prokopenko, I, Tonjes, A, Kronenberg, F, Doring, A, Rivadeneira, Fernando, Montgomery, GW, Whitfield, JB, Kahonen, M, Lehtimaki, T, Freimer, NB, Willemsen, G, de Geus, EJC, Palotie, A, Sandhu, MS, Waterworth, DM, Metspalu, A, Stumvoll, M, Uitterlinden, André, Jula, A, Navis, G, Wijmenga, C, Wolffenbuttel, BHR, Taskinen, MR, Ala-Korpela, M, Kaprio, J, Kyvik, KO, Boomsma, DI, Pedersen, NL, Gyllensten, U, Wilson, JF, Rudan, I, Campbell, H, Pramstaller, PP, Spector, TD, Witteman, JCM, Eriksson, JG, Salomaa, V, Oostra, Ben, Raitakari, OT, Wichmann, HE, Gieger, C, Jarvelin, MR, Martin, NG, Hofman, Bert, McCarthy, MI, Peltonen, L, Duijn, Cornelia, Aulchenko, YS, and Ripatti, S

Abstract

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain similar to 25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79 x 10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

Published
2011

15. Linkage of familial combined hyperlipidaemia to chromosome 1q21-q23.

Author

Pajukanta, P, Nuotio, I, Terwilliger, JD, Porkka, KV, Ylitalo, K, Pihlajamaki, J, Suomalainen, AJ, Syvänen, A-C, Lehtimaki, T, Viikari, JS, Laakso, M, Taskinen, MR, Ehnholm, C, Peltonen, L, Pajukanta, P, Nuotio, I, Terwilliger, JD, Porkka, KV, Ylitalo, K, Pihlajamaki, J, Suomalainen, AJ, Syvänen, A-C, Lehtimaki, T, Viikari, JS, Laakso, M, Taskinen, MR, Ehnholm, C, and Peltonen, L

Published
1998

16. Left ventricular mass and geometry in adolescence: early childhood determinants.

Author

Hietalampi H, Pahkala K, Jokinen E, Rönnemaa T, Viikari JS, Niinikoski H, Heinonen OJ, Salo P, Simell O, Raitakari OT, Hietalampi, Hanna, Pahkala, Katja, Jokinen, Eero, Rönnemaa, Tapani, Viikari, Jorma S A, Niinikoski, Harri, Heinonen, Olli J, Salo, Pia, Simell, Olli, and Raitakari, Olli T

Abstract

It is not known whether birth weight and early childhood growth are associated with the development of cardiac left ventricular mass (LVM) in healthy adolescents. Left ventricular growth and geometric remodeling may have long-term consequences on cardiovascular health later in life. We studied the determinants of LVM and patterns of geometric remodeling in adolescents with specific emphasis on birth size and growth in early childhood. Left ventricular measurements were obtained with echocardiography in 418 adolescents at the age of 15 years in a prospective atherosclerosis prevention study, Special Turku Coronary Risk Factor Intervention Project (STRIP). Birth weight (P=0.0004), current pulse pressure (P=0.013), physical activity level (P=0.0024), weight (P<0.0001), and male sex (P<0.001) had an independent direct association with LVM in adolescents explaining 47% of the variation. Growth in early childhood was not associated with LVM in adolescents. Birth weight (P=0.0066), current weight (P<0.0001), and physical activity level (P=0.0017) were directly associated with left ventricular posterior wall thickness. Current weight was also directly associated with septal thickness (P<0.0001). Boys had a thicker septum than girls (P=0.0092). Normal relative wall thickness and increased left ventricular mass index (eccentric remodeling) (P<0.0001), as well as increase in both variables (concentric, increased LVM) (P=0.0003), were associated with higher body mass index. Our results indicate that birth weight has a long-lasting impact on LVM and normal body weight is beneficial for cardiac structure in adolescents. [ABSTRACT FROM AUTHOR]

Published
2012
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17. Childhood nutrition in predicting metabolic syndrome in adults: the cardiovascular risk in Young Finns Study.

Author

Jääskeläinen P, Magnussen CG, Pahkala K, Mikkilä V, Kähönen M, Sabin MA, Fogelholm M, Hutri-Kähönen N, Taittonen L, Telama R, Laitinen T, Jokinen E, Lehtimäki T, Viikari JS, Raitakari OT, Juonala M, Jääskeläinen, Paula, Magnussen, Costan G, Pahkala, Katja, and Mikkilä, Vera

Abstract

Objective: Our aim was to study the associations of childhood lifestyle factors (the frequency of consumption of vegetables, fruit, fish, and meat, butter use on bread, and physical activity) with the metabolic syndrome (MetS) in adulthood.Research Design and Methods: The study cohort consisted of 2,128 individuals, 3-18 years of age at the baseline, with a follow-up time of 27 years. We used the average of lifestyle factor measurements taken in 1980, 1983, and 1986 in the analyses. Childhood dietary factors and physical activity were assessed by self-reported questionnaires, and a harmonized definition of MetS was used as the adult outcome.Results: Childhood vegetable consumption frequency was inversely associated with adult MetS (odds ratio [OR] 0.86 [95% CI 0.77-0.97], P = 0.02) in a multivariable analysis adjusted with age, sex, childhood metabolic risk factors (lipids, systolic blood pressure, insulin, BMI, and C-reactive protein), family history of type 2 diabetes and hypertension, and socioeconomic status. The association remained even after adjustment for adulthood vegetable consumption. Associations with the other childhood lifestyle factors were not found. Of the individual components of MetS, decreased frequency of childhood vegetable consumption predicted high blood pressure (0.88 [0.80-0.98], P = 0.01) and a high triglyceride value (0.88 [0.79-0.99], P = 0.03) after adjustment for the above-mentioned risk factors.Conclusions: Childhood vegetable consumption frequency is inversely associated with MetS in adulthood. Our findings suggest that a higher intake of vegetables in childhood may have a protective effect on MetS in adulthood. [ABSTRACT FROM AUTHOR]

Published
2012
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20. Influence of Age on Associations Between Childhood Risk Factors and Carotid Intima-Media Thickness in Adulthood: The Cardiovascular Risk in Young Finns Study, the Childhood Determinants of Adult Health Study, the Bogalusa Heart Study, and the Muscatine Study for the International Childhood Cardiovascular Cohort (i3C) Consortium.

Author

Juonala M, Magnussen CG, Venn A, Dwyer T, Burns TL, Davis PH, Chen W, Srinivasan SR, Daniels SR, Khnen M, Laitinen T, Taittonen L, Berenson GS, Viikari JS, and Raitakari OT

Published
2010
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22. Pediatric metabolic syndrome predicts adulthood metabolic syndrome, subclinical atherosclerosis, and type 2 diabetes mellitus but is no better than body mass index alone: the Bogalusa Heart Study and the Cardiovascular Risk in Young Finns Study.

Author

Magnussen CG, Koskinen J, Chen W, Thomson R, Schmidt MD, Srinivasan SR, Kivimäki M, Mattsson N, Kähönen M, Laitinen T, Taittonen L, Rönnemaa T, Viikari JS, Berenson GS, Juonala M, Raitakari OT, Magnussen, Costan G, Koskinen, Juha, Chen, Wei, and Thomson, Russell

Published
2010
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27. Association of age at menarche with cardiovascular risk factors, vascular structure, and function in adulthood: the Cardiovascular Risk in Young Finns study.

Author

Kivimäki M, Lawlor DA, Smith GD, Elovainio M, Jokela M, Keltikangas-Järvinen L, Vahtera J, Taittonen L, Juonala M, Viikari JS, and Raitakari OT

Abstract

BACKGROUND: It is unclear whether age at menarche is an independent determinant of future cardiovascular risk. OBJECTIVE: We aimed to determine whether menarcheal age is an independent predictor of body mass index (BMI) and a wide range of cardiovascular risk factors in adolescence and adulthood. DESIGN: We examined the associations of menarcheal age with BMI (in kg/m(2)) and other cardiovascular risk factors in adolescence and adulthood in a population-based sample of 794 female adolescents aged 9-18 y at baseline. Their age at first menstruation was requested at baseline and again 3 and 6 y later. Cardiovascular risk factors were assessed at baseline and at age 30-39 y. RESULTS: A 1-y decrease in menarcheal age was associated with 0.81 (95% CI: 0.53, 1.08) higher adult BMI as well as greater waist circumference and waist-to-hip ratio, elevated systolic blood pressure, higher insulin resistance, and greater risk of metabolic syndrome (P < 0.05 for all). In multivariable analysis in which these adult risk factors were mutually adjusted for, only the inverse association between age at menarche and adult BMI remained. However, this inverse association was lost after adjustment for premenarcheal BMI (beta: -0.16; 95% CI -0.55, 0.23; P = 0.42). Higher premenarcheal BMI predicted earlier menarche, and the strong association between premenarcheal BMI and adult BMI was robust to adjustment for age at menarche. CONCLUSIONS: These findings suggest that early menarche is only a risk marker. Greater childhood BMI seems to contribute to earlier age at menarche and, because of tracking, greater adult BMI and associated cardiovascular risk. An independent effect of early menarche on adult adiposity cannot be excluded, but it is likely to be small at best. Copyright © 2008 American Society for Nutrition [ABSTRACT FROM AUTHOR]

Published
2008

28. Variants in the CRP Gene as a Measure of Lifelong Differences in Average C-Reactive Protein Levels: The Cardiovascular Risk in Young Finns Study, 1980 2001.

Author

Kivimäki M, Lawlor DA, Smith GD, Eklund C, Hurme M, Lehtimäki T, Viikari JS, and Raitakari OT

Abstract

Genetic association studies have used variants in the C-reactive protein (CRP) gene to estimate causal effects of lifelong circulating CRP levels on disease endpoints. However, the extent to which the genetic variants are actually associated with lifelong circulating CRP levels has not been demonstrated empirically. In a population-based prospective cohort study (1980-2001) of 1,609 young Finns (768 men and 841 women), the authors genotyped five single nucleotide polymorphisms in the CRP gene (-717A/G, -286C/T/A, +1059G/C, +1444T/C, and +1846G/A) and assessed circulating CRP levels at ages 3-18 years and 24-39 years. The haplotypes from the five single nucleotide polymorphisms were associated with circulating CRP levels in childhood and adulthood, with the strongest effect being found for average CRP level across these two measures taken at two time points in the life course. In combination, the haplotype pairs accounted for 3.9%, 3.3%, and 5.0% of the variation in circulating CRP levels in childhood, in adulthood, and for the mean of CRP levels at both time points, respectively. These findings support the assumption that the above genetic variants define groups with long-term differences in circulating CRP levels. [ABSTRACT FROM AUTHOR]

Published
2007
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30. Endothelial function in healthy 11-year-old children after dietary intervention with onset in infancy: the Special Turku Coronary Risk Factor Intervention Project for children (STRIP).

Author

Raitakari OT, Rönnemaa T, Järvisalo MJ, Kaitosaari T, Volanen I, Kallio K, Lagström H, Jokinen E, Niinikoski H, Viikari JS, Simell O, Raitakari, Olli T, Rönnemaa, Tapani, Järvisalo, Mikko J, Kaitosaari, Tuuli, Volanen, Iina, Kallio, Katariina, Lagström, Hanna, Jokinen, Eero, and Niinikoski, Harri

Published
2005

34. Genome-wide associations for birth weight and correlations with adult disease

Author

Horikoshi, M, Beaumont, RN, Day, FR, Warrington, NM, Kooijman, MN, Fernandez-Tajes, J, Feenstra, B, Van Zuydam, NR, Gaulton, KJ, Grarup, N, Bradfield, JP, Strachan, DP, Li-Gao, R, Ahluwalia, TS, Kreiner, E, Rueedi, R, Lyytikäinen, L-P, Cousminer, DL, Wu, Y, Thiering, E, Wang, CA, Have, CT, Hottenga, J-J, Vilor-Tejedor, N, Joshi, PK, Boh, ETH, Ntalla, I, Pitkänen, N, Mahajan, A, Van Leeuwen, EM, Joro, R, Lagou, V, Nodzenski, M, Diver, LA, Zondervan, KT, Bustamante, M, Marques-Vidal, P, Mercader, JM, Bennett, AJ, Rahmioglu, N, Nyholt, DR, Ma, RCW, Tam, CHT, Tam, WH, CHARGE Consortium Hematology Working Group, Ganesh, SK, Van Rooij, FJA, Jones, SE, Loh, P-R, Ruth, KS, Tuke, MA, Tyrrell, J, Wood, AR, Yaghootkar, H, Scholtens, DM, Paternoster, L, Prokopenko, I, Kovacs, P, Atalay, M, Willems, SM, Panoutsopoulou, K, Wang, X, Carstensen, L, Geller, F, Schraut, KE, Murcia, M, Van Beijsterveldt, CEM, Willemsen, G, Appel, EVR, Fonvig, CE, Trier, C, Tiesler, CMT, Standl, M, Kutalik, Z, Bonàs-Guarch, S, Hougaard, DM, Sánchez, F, Torrents, D, Waage, J, Hollegaard, MV, De Haan, HG, Rosendaal, FR, Medina-Gomez, C, Ring, SM, Hemani, G, McMahon, G, Robertson, NR, Groves, CJ, Langenberg, C, Luan, J, Scott, RA, Zhao, JH, Mentch, FD, MacKenzie, SM, Reynolds, RM, Early Growth Genetics (EGG) Consortium, Lowe, WL, Tönjes, A, Stumvoll, M, Lindi, V, Lakka, TA, Van Duijn, CM, Kiess, W, Körner, A, Sørensen, TIA, Niinikoski, H, Pahkala, K, Raitakari, OT, Zeggini, E, Dedoussis, GV, Teo, Y-Y, Saw, S-M, Melbye, M, Campbell, H, Wilson, JF, Vrijheid, M, De Geus, EJCN, Boomsma, DI, Kadarmideen, HN, Holm, J-C, Hansen, T, Sebert, S, Hattersley, AT, Beilin, LJ, Newnham, JP, Pennell, CE, Heinrich, J, Adair, LS, Borja, JB, Mohlke, KL, Eriksson, JG, Widén, E, Kähönen, M, Viikari, JS, Lehtimäki, T, Vollenweider, P, Bønnelykke, K, Bisgaard, H, Mook-Kanamori, DO, Hofman, A, Rivadeneira, F, Uitterlinden, AG, Pisinger, C, Pedersen, O, Power, C, Hyppönen, E, Wareham, NJ, Hakonarson, H, Davies, E, Walker, BR, Jaddoe, VWV, Järvelin, M-R, Grant, SFA, Vaag, AA, Lawlor, DA, Frayling, TM, Smith, GD, Morris, AP, Ong, KK, Felix, JF, Timpson, NJ, Perry, JRB, Evans, DM, McCarthy, MI, and Freathy, RM

Subjects
quantitative trait, hypertension, intrauterine growth, genome-wide association studies, metabolic disorders, 3. Good health
Abstract

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW ($\textit{P}$ < 5 × 10$^{-8}$). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure ($\textit{R}$ $_{g}$ = -0.22, $\textit{P}$ = 5.5 × 10$^{-13}$), T2D ($\textit{R}$ $_{g}$ = -0.27, $\textit{P}$ = 1.1 × 10$^{-6}$) and coronary artery disease ($\textit{R}$ $_{g}$ = -0.30, $\textit{P}$ = 6.5 × 10$^{-9}$). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions ($\textit{P}$ = 1.9 × 10$^{-4}$). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

35. Association of Pathobiologic Determinants of Atherosclerosis in Youth risk score and 15-year change in risk score with carotid artery intima-media thickness in young adults (from the Cardiovascular Risk in Young Finns Study).

Author

McMahan CA, Gidding SS, Viikari JS, Juonala M, Kähönen M, Hutri-Kähönen N, Jokinen E, Taittonen L, Pietikäinen M, McGill HC Jr, Raitakari OT, McMahan, C Alex, Gidding, Samuel S, Viikari, Jorma S A, Juonala, Markus, Kähönen, Mika, Hutri-Kähönen, Nina, Jokinen, Eero, Taittonen, Leena, and Pietikäinen, Matti

Abstract

The Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study of autopsy findings in subjects 15 to 34 years of age developed a risk score using coronary heart disease risk factors (gender, age, serum lipoprotein concentrations, smoking, hypertension, obesity, and hyperglycemia) to estimate the probability of advanced atherosclerotic lesions in the coronary arteries. The Cardiovascular Risk in Young Finns Study measured coronary heart disease risk factors in a population-based cohort in 1986 and 2001 and measured carotid artery intima-media thickness (IMT) with ultrasonography in 2001. We computed the PDAY risk score from risk factors measured in 1,279 subjects who were 12 to 24 years of age in 1986 and 27 to 39 years of age in 2001. The PDAY risk score early in life (i.e., 1986) and the change in risk score in the following 15 years (i.e., 1986 through 2001) were independent predictors of carotid artery intima-media thickness; the multiplicative effect of 1 point in the 1986 risk score was 1.008 (95% confidence interval 1.005 to 1.012) and the multiplicative effect of a 1-point increase between the 1986 and 2001 risk scores was 1.003 (95% confidence interval 1.001 to 1.006; multiplicative effect of 0.997 for a 1-point decrease). In conclusion, the change in risk score over time (decrease or increase) during adolescence and young adulthood, as well as the risk score early in life, are important predictors of atherosclerosis. [ABSTRACT FROM AUTHOR]

Published
2007
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36. The association of pediatric low- and high-density lipoprotein cholesterol dyslipidemia classifications and change in dyslipidemia status with carotid intima-media thickness in adulthood evidence from the cardiovascular risk in Young Finns study, the Bogalusa Heart study, and the CDAH (Childhood Determinants of Adult Health) study.

Author

Magnussen CG, Venn A, Thomson R, Juonala M, Srinivasan SR, Viikari JS, Berenson GS, Dwyer T, Raitakari OT, Magnussen, Costan G, Venn, Alison, Thomson, Russell, Juonala, Markus, Srinivasan, Sathanur R, Viikari, Jorma S A, Berenson, Gerald S, Dwyer, Terence, and Raitakari, Olli T

Abstract

Objectives: This study was designed to determine which of the National Cholesterol Education Program or National Health and Nutrition Examination Survey low- and high-density lipoprotein cholesterol classifications of dyslipidemia status in adolescents is most effective at predicting high common carotid artery intima-media thickness (IMT) in adulthood.Background: Two classifications of pediatric dyslipidemia status have been proposed. No study has assessed which of these is most effective for predicting adolescents who will develop preclinical atherosclerosis in adulthood.Methods: Three population-based, prospective cohort studies collected lipoprotein measurements on 1,711 adolescents age 12 to 18 years who were remeasured as young adults age 29 to 39 years. Lipoproteins in adolescence were classified according to National Cholesterol Education Program and National Health and Nutrition Examination Survey cut points, and high IMT in adulthood was defined as those at or above the age-, sex-, race-, and cohort-specific 90th percentile of IMT.Results: Independent of the classification employed, adolescents with dyslipidemia were at significantly increased risk of having high IMT in adulthood (relative risks from 1.6 to 2.5). Differences in predictive capacity between both classifications were minimal. Overweight or obese adolescents with dyslipidemia had increased carotid IMT (males: 0.11 mm; females: 0.08 mm) in adulthood compared with those who did not have both risk factors. Adolescent dyslipidemia status was more strongly associated with high IMT in adulthood than change in dyslipidemia status.Conclusions: Pediatric dyslipidemia classifications perform equally in the prediction of adolescents who are at increased risk of high IMT in young adulthood. Our data suggest that dyslipidemia screening could be limited to overweight or obese adolescents. [ABSTRACT FROM AUTHOR]

Published
2009
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37. Association of number of siblings with preclinical markers of cardiovascular disease. The cardiovascular risk in Young Finns study.

Author

Pihlman J, Magnussen CG, Laitinen TT, Ruohonen S, Pahkala K, Jokinen E, Laitinen TP, Hutri-Kähönen N, Tossavainen P, Taittonen L, Kähönen M, Viikari JS, Raitakari OT, Juonala M, and Nuotio J

Abstract

To investigate the association of number of siblings with preclinical cardiovascular disease (CVD) markers in adulthood. The sample comprised 2776 participants (54 % female) from the Cardiovascular Risk in Young Finns Study who had CVD risk factor data measured in childhood in 1980 (aged 3-18 years) and markers of preclinical CVD measured in adulthood. Echocardiography was performed in 2011, and carotid intima-media thickness, carotid distensibility, brachial flow-mediated dilatation, and arterial pulse wave velocity were measured in 2001 or 2007. The association between the number of siblings and preclinical CVD was assessed using generalized linear and logistic regression models. Analyses were stratified by sex as associations differed between sexes. Women with 1 sibling had lower E/e'-ratio (4.9, [95%CI 4.8-5.0]) in echocardiography compared with those without siblings (5.1[4.9-5.2]) and those with ≥2 more siblings (5.1[5.0-5.2]) (P for trend 0.01). Men without siblings had the lowest E/A-ratio (1.4[1.3-1.5]) compared with those with 1 sibling (1.5[1.5-1.5]), or ≥2 siblings (1.5[1.5-1.5]) (P for trend 0.01). Women without siblings had highest left ventricular ejection fraction (59.2 %[58.6-59.7 %]) compared with those with 1 sibling (59.1 %[58.8-59.4 %]), or ≥2 siblings (58.4 %[58.1-58.8 %])(P for trend 0.01). In women, brachial flow-mediated dilatation, a measure of endothelial function, was the lowest among participants with ≥2 siblings (9.4 %[9.0-9.8 %]) compared with those with 1 sibling (10.0 %[9.6-10.3 %]) and those without siblings (10.4 %[9.7-11.0 %])(P for trend 0.03). We observed that number of siblings may be associated with increased risk of heart failure in women. As the associations were somewhat inconsistent in males and females, further research is warranted., Competing Interests: The authors declared they do not have anything to disclose regarding no conflict of interest with respect to this manuscript., (© 2023 The Authors.)

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

Author

Haslam DE, Peloso GM, Guirette M, Imamura F, Bartz TM, Pitsillides AN, Wang CA, Li-Gao R, Westra JM, Pitkänen N, Young KL, Graff M, Wood AC, Braun KVE, Luan J, Kähönen M, Kiefte-de Jong JC, Ghanbari M, Tintle N, Lemaitre RN, Mook-Kanamori DO, North K, Helminen M, Mossavar-Rahmani Y, Snetselaar L, Martin LW, Viikari JS, Oddy WH, Pennell CE, Rosendall FR, Ikram MA, Uitterlinden AG, Psaty BM, Mozaffarian D, Rotter JI, Taylor KD, Lehtimäki T, Raitakari OT, Livingston KA, Voortman T, Forouhi NG, Wareham NJ, de Mutsert R, Rich SS, Manson JE, Mora S, Ridker PM, Merino J, Meigs JB, Dashti HS, Chasman DI, Lichtenstein AH, Smith CE, Dupuis J, Herman MA, and McKeown NM

Subjects
Adult, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors metabolism, Cholesterol, HDL genetics, Female, Humans, Male, Meta-Analysis as Topic, Middle Aged, Triglycerides genetics, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors genetics, Cholesterol, HDL blood, Polymorphism, Single Nucleotide, Sugar-Sweetened Beverages adverse effects, Triglycerides blood
Abstract

Background: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the CHREBP locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the CHREBP locus and dyslipidemia., Methods: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near CHREBP were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake., Results: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; P <0.0001), but not significantly among the lowest SSB consumers ( P =0.81; P Diff <0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (β, 0.06 [95% CI, 0.02-0.09] ln-mg/dL per allele, P =0.001) but not the lowest SSB consumers ( P =0.84; P Diff =0.0005)., Conclusions: Our results identified genetic variants in the CHREBP locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005133, NCT00005121, NCT00005487, and NCT00000479.

Published
2021
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39. The Role of Inflammatory Cytokines as Intermediates in the Pathway from Increased Adiposity to Disease.

Author

Kalaoja M, Corbin LJ, Tan VY, Ahola-Olli AV, Havulinna AS, Santalahti K, Pitkänen N, Lehtimäki T, Lyytikäinen LP, Raitoharju E, Seppälä I, Kähönen M, Ripatti S, Palotie A, Perola M, Viikari JS, Jalkanen S, Maksimow M, Salomaa V, Salmi M, Raitakari OT, Kettunen J, and Timpson NJ

Subjects
Body Mass Index, Cohort Studies, Humans, Adiposity physiology, Cytokines blood, Obesity complications
Abstract

Objective: This study aimed to investigate the role of cytokines as intermediates in the pathway from increased adiposity to disease., Methods: BMI and circulating levels of up to 41 cytokines were measured in individuals from three Finnish cohort studies (n = 8,293). Mendelian randomization (MR) was used to assess the impact of BMI on circulating cytokines and the impact of BMI-driven cytokines on risk of obesity-related diseases., Results: Observationally, BMI was associated with 19 cytokines. For every SD increase in BMI, causal effect estimates were strongest for hepatocyte growth factor, monocyte chemotactic protein-1 (MCP-1), and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and were as ratios of geometric means 1.13 (95% CI: 1.08-1.19), 1.08 (95% CI: 1.04-1.14), and 1.13 (95% CI: 1.04-1.21), respectively. TRAIL was associated with a small increase in the odds of coronary artery disease (odds ratio: 1.03; 95% CI: 1.00-1.06). There was inconsistent evidence for a protective role of MCP-1 against inflammatory bowel diseases., Conclusions: Observational and MR estimates of the effect of BMI on cytokine levels were generally concordant. There was little evidence for an effect of raised levels of BMI-driven cytokines on disease. These findings illustrate the challenges of MR when applied in the context of molecular mediation., (© 2021 The Authors. Obesity published by Wiley Periodicals LLC on behalf of The Obesity Society (TOS).)

Published
2021
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40. Apolipoprotein A-I concentrations and risk of coronary artery disease: A Mendelian randomization study.

Author

Karjalainen MK, Holmes MV, Wang Q, Anufrieva O, Kähönen M, Lehtimäki T, Havulinna AS, Kristiansson K, Salomaa V, Perola M, Viikari JS, Raitakari OT, Järvelin MR, Ala-Korpela M, and Kettunen J

Subjects
Humans, Biomarkers blood, Finland epidemiology, Genetic Predisposition to Disease, Genome-Wide Association Study, Incidence, Mendelian Randomization Analysis, Phenotype, Prognosis, Protective Factors, Risk Assessment, Risk Factors, Apolipoprotein A-I blood, Apolipoprotein A-I genetics, Apolipoprotein A-I therapeutic use, Coronary Artery Disease blood, Coronary Artery Disease epidemiology, Coronary Artery Disease genetics, Coronary Artery Disease prevention & control, Polymorphism, Single Nucleotide
Abstract

Background and Aims: Apolipoprotein A-I (apoA-I) infusions represent a potential novel therapeutic approach for the prevention of coronary artery disease (CAD). Although circulating apoA-I concentrations inversely associate with risk of CAD, the evidence base of this representing a causal relationship is lacking. The aim was to assess the causal role of apoA-I using human genetics., Methods: We identified a variant (rs12225230) in APOA1 locus that associated with circulating apoA-I concentrations (p < 5 × 10 -8 ) in 20,370 Finnish participants, and meta-analyzed our data with a previous GWAS of apoA-I. We obtained genetic estimates of CAD from UK Biobank and CARDIoGRAMplusC4D (totaling 122,733 CAD cases) and conducted a two-sample Mendelian randomization analysis. We compared our genetic findings to observational associations of apoA-I with risk of CAD in 918 incident CAD cases among 11,535 individuals from population-based prospective cohorts., Results: ApoA-I was associated with a lower risk of CAD in observational analyses (HR 0.81; 95%CI: 0.75, 0.88; per 1-SD higher apoA-I), with the association showing a dose-response relationship. Rs12225230 associated with apoA-I concentrations (per-C allele beta 0.076 SD; SE: 0.013; p = 1.5 × 10 -9 ) but not with confounders. In Mendelian randomization analyses, apoA-I was not related to risk of CAD (OR 1.13; 95%CI: 0.98,1.30 per 1-SD higher apoA-I), which was different from the observational association. Similar findings were observed using an independent ABCA1 variant in sensitivity analysis., Conclusions: Genetic evidence fails to support a cardioprotective role for apoA-I. This is in line with the cumulative evidence showing that HDL-related phenotypes are unlikely to have a protective role in CAD., Competing Interests: Declaration of competing interest VS has participated in a conference trip sponsored by Novo Nordisk and received an honorarium for participating in an advisory board meeting (unrelated to the present study). He also has ongoing research collaboration with Bayer Ltd (unrelated to the present study). No other authors reported conflicts of interest., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2020
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41. Multivariate Genome-wide Association Analysis of a Cytokine Network Reveals Variants with Widespread Immune, Haematological, and Cardiometabolic Pleiotropy.

Author

Nath AP, Ritchie SC, Grinberg NF, Tang HH, Huang QQ, Teo SM, Ahola-Olli AV, Würtz P, Havulinna AS, Santalahti K, Pitkänen N, Lehtimäki T, Kähönen M, Lyytikäinen LP, Raitoharju E, Seppälä I, Sarin AP, Ripatti S, Palotie A, Perola M, Viikari JS, Jalkanen S, Maksimow M, Salmi M, Wallace C, Raitakari OT, Salomaa V, Abraham G, Kettunen J, and Inouye M

Subjects
Adolescent, Adult, Aged, Blood Proteins genetics, Blood Proteins immunology, Cardiovascular Diseases immunology, Cardiovascular Diseases pathology, Child, Cytokines immunology, Female, Follow-Up Studies, Gene Regulatory Networks, Genetic Predisposition to Disease, Genome, Human, Humans, Longitudinal Studies, Male, Middle Aged, Prognosis, Prospective Studies, Young Adult, Biomarkers analysis, Cardiovascular Diseases genetics, Cytokines genetics, Genetic Pleiotropy, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Quantitative Trait Loci
Abstract

Cytokines are essential regulatory components of the immune system, and their aberrant levels have been linked to many disease states. Despite increasing evidence that cytokines operate in concert, many of the physiological interactions between cytokines, and the shared genetic architecture that underlies them, remain unknown. Here, we aimed to identify and characterize genetic variants with pleiotropic effects on cytokines. Using three population-based cohorts (n = 9,263), we performed multivariate genome-wide association studies (GWAS) for a correlation network of 11 circulating cytokines, then combined our results in meta-analysis. We identified a total of eight loci significantly associated with the cytokine network, of which two (PDGFRB and ABO) had not been detected previously. In addition, conditional analyses revealed a further four secondary signals at three known cytokine loci. Integration, through the use of Bayesian colocalization analysis, of publicly available GWAS summary statistics with the cytokine network associations revealed shared causal variants between the eight cytokine loci and other traits; in particular, cytokine network variants at the ABO, SERPINE2, and ZFPM2 loci showed pleiotropic effects on the production of immune-related proteins, on metabolic traits such as lipoprotein and lipid levels, on blood-cell-related traits such as platelet count, and on disease traits such as coronary artery disease and type 2 diabetes., (Copyright © 2019 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2019
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42. 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 J, Dashti HS, Li SX, Sarnowski C, Justice AE, Graff M, Papoutsakis C, Smith CE, Dedoussis GV, Lemaitre RN, Wojczynski MK, Männistö S, Ngwa JS, Kho M, Ahluwalia TS, Pervjakova N, Houston DK, Bouchard C, Huang T, Orho-Melander M, Frazier-Wood AC, Mook-Kanamori DO, Pérusse L, Pennell CE, de Vries PS, Voortman T, Li O, Kanoni S, Rose LM, Lehtimäki T, Zhao JH, Feitosa MF, Luan J, McKeown NM, Smith JA, Hansen T, Eklund N, Nalls MA, Rankinen T, Huang J, Hernandez DG, Schulz CA, Manichaikul A, Li-Gao R, Vohl MC, Wang CA, van Rooij FJA, Shin J, Kalafati IP, Day F, Ridker PM, Kähönen M, Siscovick DS, Langenberg C, Zhao W, Astrup A, Knekt P, Garcia M, Rao DC, Qi Q, Ferrucci L, Ericson U, Blangero J, Hofman A, Pausova Z, Mikkilä V, Wareham NJ, Kardia SLR, Pedersen O, Jula A, Curran JE, Zillikens MC, Viikari JS, Forouhi NG, Ordovás JM, Lieske JC, Rissanen H, Uitterlinden AG, Raitakari OT, Kiefte-de Jong JC, Dupuis J, Rotter JI, North KE, Scott RA, Province MA, Perola M, Cupples LA, Turner ST, Sørensen TIA, Salomaa V, Liu Y, Sung YJ, Qi L, Bandinelli S, Rich SS, de Mutsert R, Tremblay A, Oddy WH, Franco OH, Paus T, Florez JC, Deloukas P, Lyytikäinen LP, Chasman DI, Chu AY, and Tanaka T

Subjects
Aged, Alpha-Ketoglutarate-Dependent Dioxygenase FTO genetics, Cohort Studies, Energy Intake genetics, Female, Fibroblast Growth Factors genetics, Genetic Loci genetics, Genetic Predisposition to Disease epidemiology, Genetic Predisposition to Disease genetics, Genome-Wide Association Study, Genomics methods, Genotype, Heart Diseases epidemiology, Humans, Male, Membrane Proteins genetics, Middle Aged, Obesity genetics, Polymorphism, Single Nucleotide genetics, Receptors, Retinoic Acid genetics, White People genetics, Aging genetics, Heart Diseases genetics, Nutrients
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 RARB locus for carbohydrate intake and a rare variant in DRAM1 locus for protein intake, and corroborating earlier FGF21 and FTO findings. 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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43. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.

Author

Warrington NM, Beaumont RN, Horikoshi M, Day FR, Helgeland Ø, Laurin C, Bacelis J, Peng S, Hao K, Feenstra B, Wood AR, Mahajan A, Tyrrell J, Robertson NR, Rayner NW, Qiao Z, Moen GH, Vaudel M, Marsit CJ, Chen J, Nodzenski M, Schnurr TM, Zafarmand MH, Bradfield JP, Grarup N, Kooijman MN, Li-Gao R, Geller F, Ahluwalia TS, Paternoster L, Rueedi R, Huikari V, Hottenga JJ, Lyytikäinen LP, Cavadino A, Metrustry S, Cousminer DL, Wu Y, Thiering E, Wang CA, Have CT, Vilor-Tejedor N, Joshi PK, Painter JN, Ntalla I, Myhre R, Pitkänen N, van Leeuwen EM, Joro R, Lagou V, Richmond RC, Espinosa A, Barton SJ, Inskip HM, Holloway JW, Santa-Marina L, Estivill X, Ang W, Marsh JA, Reichetzeder C, Marullo L, Hocher B, Lunetta KL, Murabito JM, Relton CL, Kogevinas M, Chatzi L, Allard C, Bouchard L, Hivert MF, Zhang G, Muglia LJ, Heikkinen J, Morgen CS, van Kampen AHC, van Schaik BDC, Mentch FD, Langenberg C, Luan J, Scott RA, Zhao JH, Hemani G, Ring SM, Bennett AJ, Gaulton KJ, Fernandez-Tajes J, van Zuydam NR, Medina-Gomez C, de Haan HG, Rosendaal FR, Kutalik Z, Marques-Vidal P, Das S, Willemsen G, Mbarek H, Müller-Nurasyid M, Standl M, Appel EVR, Fonvig CE, Trier C, van Beijsterveldt CEM, Murcia M, Bustamante M, Bonas-Guarch S, Hougaard DM, Mercader JM, Linneberg A, Schraut KE, Lind PA, Medland SE, Shields BM, Knight BA, Chai JF, Panoutsopoulou K, Bartels M, Sánchez F, Stokholm J, Torrents D, Vinding RK, Willems SM, Atalay M, Chawes BL, Kovacs P, Prokopenko I, Tuke MA, Yaghootkar H, Ruth KS, Jones SE, Loh PR, Murray A, Weedon MN, Tönjes A, Stumvoll M, Michaelsen KF, Eloranta AM, Lakka TA, van Duijn CM, Kiess W, Körner A, Niinikoski H, Pahkala K, Raitakari OT, Jacobsson B, Zeggini E, Dedoussis GV, Teo YY, Saw SM, Montgomery GW, Campbell H, Wilson JF, Vrijkotte TGM, Vrijheid M, de Geus EJCN, Hayes MG, Kadarmideen HN, Holm JC, Beilin LJ, Pennell CE, Heinrich J, Adair LS, Borja JB, Mohlke KL, Eriksson JG, Widén EE, Hattersley AT, Spector TD, Kähönen M, Viikari JS, Lehtimäki T, Boomsma DI, Sebert S, Vollenweider P, Sørensen TIA, Bisgaard H, Bønnelykke K, Murray JC, Melbye M, Nohr EA, Mook-Kanamori DO, Rivadeneira F, Hofman A, Felix JF, Jaddoe VWV, Hansen T, Pisinger C, Vaag AA, Pedersen O, Uitterlinden AG, Järvelin MR, Power C, Hyppönen E, Scholtens DM, Lowe WL Jr, Davey Smith G, Timpson NJ, Morris AP, Wareham NJ, Hakonarson H, Grant SFA, Frayling TM, Lawlor DA, Njølstad PR, Johansson S, Ong KK, McCarthy MI, Perry JRB, Evans DM, and Freathy RM

Subjects
Adult, Blood Pressure genetics, Body Height genetics, Diabetes Mellitus, Type 2 etiology, Diabetes Mellitus, Type 2 genetics, Female, Fetal Development genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Heart Diseases etiology, Heart Diseases genetics, Humans, Infant, Newborn, Male, Maternal Inheritance genetics, Maternal-Fetal Exchange genetics, Metabolic Diseases etiology, Metabolic Diseases genetics, Models, Genetic, Polymorphism, Single Nucleotide, Pregnancy, Risk Factors, Birth Weight genetics
Abstract

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

Published
2019
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44. CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits.

Author

Macé A, Tuke MA, Deelen P, Kristiansson K, Mattsson H, Nõukas M, Sapkota Y, Schick U, Porcu E, Rüeger S, McDaid AF, Porteous D, Winkler TW, Salvi E, Shrine N, Liu X, Ang WQ, Zhang W, Feitosa MF, Venturini C, van der Most PJ, Rosengren A, Wood AR, Beaumont RN, Jones SE, Ruth KS, Yaghootkar H, Tyrrell J, Havulinna AS, Boers H, Mägi R, Kriebel J, Müller-Nurasyid M, Perola M, Nieminen M, Lokki ML, Kähönen M, Viikari JS, Geller F, Lahti J, Palotie A, Koponen P, Lundqvist A, Rissanen H, Bottinger EP, Afaq S, Wojczynski MK, Lenzini P, Nolte IM, Sparsø T, Schupf N, Christensen K, Perls TT, Newman AB, Werge T, Snieder H, Spector TD, Chambers JC, Koskinen S, Melbye M, Raitakari OT, Lehtimäki T, Tobin MD, Wain LV, Sinisalo J, Peters A, Meitinger T, Martin NG, Wray NR, Montgomery GW, Medland SE, Swertz MA, Vartiainen E, Borodulin K, Männistö S, Murray A, Bochud M, Jacquemont S, Rivadeneira F, Hansen TF, Oldehinkel AJ, Mangino M, Province MA, Deloukas P, Kooner JS, Freathy RM, Pennell C, Feenstra B, Strachan DP, Lettre G, Hirschhorn J, Cusi D, Heid IM, Hayward C, Männik K, Beckmann JS, Loos RJF, Nyholt DR, Metspalu A, Eriksson JG, Weedon MN, Salomaa V, Franke L, Reymond A, Frayling TM, and Kutalik Z

Subjects
Anthropometry, Body Mass Index, Body Size genetics, Chromosomes, Human, Pair 1 genetics, Chromosomes, Human, Pair 11 genetics, Chromosomes, Human, Pair 16 genetics, Chromosomes, Human, Pair 18 genetics, Chromosomes, Human, Pair 22 genetics, Chromosomes, Human, Pair 3 genetics, Chromosomes, Human, Pair 7 genetics, DNA Copy Number Variations, Genome-Wide Association Study, Genotype, Humans, Phenotype, Waist-Hip Ratio, Body Height genetics, Body Weight genetics, White People genetics
Abstract

There are few examples of robust associations between rare copy number variants (CNVs) and complex continuous human traits. Here we present a large-scale CNV association meta-analysis on anthropometric traits in up to 191,161 adult samples from 26 cohorts. The study reveals five CNV associations at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m 2 ). Burden analysis shows a 0.41 cm decrease in height, a 0.003 increase in waist-to-hip ratio and increase in BMI by 0.14 kg/m 2 for each Mb of total deletion burden (P = 2.5 × 10 -10 , 6.0 × 10 -5 , and 2.9 × 10 -3 ). Our study provides evidence that the same genes (e.g., MC4R, FIBIN, and FMO5) harbor both common and rare variants affecting body size and that anthropometric traits share genetic loci with developmental and psychiatric disorders.Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.

Published
2017
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45. Prediction of Adult Dyslipidemia Using Genetic and Childhood Clinical Risk Factors: The Cardiovascular Risk in Young Finns Study.

Author

Nuotio J, Pitkänen N, Magnussen CG, Buscot MJ, Venäläinen MS, Elo LL, Jokinen E, Laitinen T, Taittonen L, Hutri-Kähönen N, Lyytikäinen LP, Lehtimäki T, Viikari JS, Juonala M, and Raitakari OT

Subjects
Adolescent, Adult, Area Under Curve, Body Mass Index, Child, Child, Preschool, Cholesterol, HDL blood, Dyslipidemias genetics, Exercise, Female, Finland, Follow-Up Studies, Humans, Lipids blood, Male, Middle Aged, Polymorphism, Single Nucleotide, ROC Curve, Risk Factors, Smoking, Triglycerides blood, Young Adult, Dyslipidemias etiology
Abstract

Background: Dyslipidemia is a major modifiable risk factor for cardiovascular disease. We examined whether the addition of novel single-nucleotide polymorphisms for blood lipid levels enhances the prediction of adult dyslipidemia in comparison to childhood lipid measures., Methods and Results: Two thousand four hundred and twenty-two participants of the Cardiovascular Risk in Young Finns Study who had participated in 2 surveys held during childhood (in 1980 when aged 3-18 years and in 1986) and at least once in a follow-up study in adulthood (2001, 2007, and 2011) were included. We examined whether inclusion of a lipid-specific weighted genetic risk score based on 58 single-nucleotide polymorphisms for low-density lipoprotein cholesterol, 71 single-nucleotide polymorphisms for high-density lipoprotein cholesterol, and 40 single-nucleotide polymorphisms for triglycerides improved the prediction of adult dyslipidemia compared with clinical childhood risk factors. Adjusting for age, sex, body mass index, physical activity, and smoking in childhood, childhood lipid levels, and weighted genetic risk scores were associated with an increased risk of adult dyslipidemia for all lipids. Risk assessment based on 2 childhood lipid measures and the lipid-specific weighted genetic risk scores improved the accuracy of predicting adult dyslipidemia compared with the approach using only childhood lipid measures for low-density lipoprotein cholesterol (area under the receiver-operating characteristic curve 0.806 versus 0.811; P =0.01) and triglycerides (area under the receiver-operating characteristic curve 0.740 versus area under the receiver-operating characteristic curve 0.758; P <0.01). The overall net reclassification improvement and integrated discrimination improvement were significant for all outcomes., Conclusions: The inclusion of weighted genetic risk scores to lipid-screening programs in childhood could modestly improve the identification of those at highest risk of dyslipidemia in adulthood., (© 2017 American Heart Association, Inc.)

Published
2017
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46. Corrigendum: 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function.

Author

Gorski M, Most PJV, Teumer A, Chu AY, Li M, Mijatovic V, Nolte IM, Cocca M, Taliun D, Gomez F, Li Y, Tayo B, Tin A, Feitosa MF, Aspelund T, Attia J, Biffar R, Bochud M, Boerwinkle E, Borecki I, Bottinger EP, Chen MH, Chouraki V, Ciullo M, Coresh J, Cornelis MC, Curhan GC, Adamo AP, Dehghan A, Dengler L, Ding J, Eiriksdottir G, Endlich K, Enroth S, Esko T, Franco OH, Gasparini P, Gieger C, Girotto G, Gottesman O, Gudnason V, Gyllensten U, Hancock SJ, Harris TB, Helmer C, Höllerer S, Hofer E, Hofman A, Holliday EG, Homuth G, Hu FB, Huth C, Hutri-Kähönen N, Hwang SJ, Imboden M, Johansson Å, Kähönen M, König W, Kramer H, Krämer BK, Kumar A, Kutalik Z, Lambert JC, Launer LJ, Lehtimäki T, de Borst MH, Navis G, Swertz M, Liu Y, Lohman K, Loos RJF, Lu Y, Lyytikäinen LP, McEvoy MA, Meisinger C, Meitinger T, Metspalu A, Metzger M, Mihailov E, Mitchell P, Nauck M, Oldehinkel AJ, Olden M, Wjh Penninx B, Pistis G, Pramstaller PP, Probst-Hensch N, Raitakari OT, Rettig R, Ridker PM, Rivadeneira F, Robino A, Rosas SE, Ruderfer D, Ruggiero D, Saba Y, Sala C, Schmidt H, Schmidt R, Scott RJ, Sedaghat S, Smith AV, Sorice R, Stengel B, Stracke S, Strauch K, Toniolo D, Uitterlinden AG, Ulivi S, Viikari JS, Völker U, Vollenweider P, Völzke H, Vuckovic D, Waldenberger M, Wang JJ, Yang Q, Chasman DI, Tromp G, Snieder H, Heid IM, Fox CS, Köttgen A, Pattaro C, Böger CA, and Fuchsberger C

Abstract

This corrects the article DOI: 10.1038/srep45040.

Published
2017
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47. 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function.

Author

Gorski M, van der Most PJ, Teumer A, Chu AY, Li M, Mijatovic V, Nolte IM, Cocca M, Taliun D, Gomez F, Li Y, Tayo B, Tin A, Feitosa MF, Aspelund T, Attia J, Biffar R, Bochud M, Boerwinkle E, Borecki I, Bottinger EP, Chen MH, Chouraki V, Ciullo M, Coresh J, Cornelis MC, Curhan GC, d'Adamo AP, Dehghan A, Dengler L, Ding J, Eiriksdottir G, Endlich K, Enroth S, Esko T, Franco OH, Gasparini P, Gieger C, Girotto G, Gottesman O, Gudnason V, Gyllensten U, Hancock SJ, Harris TB, Helmer C, Höllerer S, Hofer E, Hofman A, Holliday EG, Homuth G, Hu FB, Huth C, Hutri-Kähönen N, Hwang SJ, Imboden M, Johansson Å, Kähönen M, König W, Kramer H, Krämer BK, Kumar A, Kutalik Z, Lambert JC, Launer LJ, Lehtimäki T, de Borst M, Navis G, Swertz M, Liu Y, Lohman K, Loos RJF, Lu Y, Lyytikäinen LP, McEvoy MA, Meisinger C, Meitinger T, Metspalu A, Metzger M, Mihailov E, Mitchell P, Nauck M, Oldehinkel AJ, Olden M, Wjh Penninx B, Pistis G, Pramstaller PP, Probst-Hensch N, Raitakari OT, Rettig R, Ridker PM, Rivadeneira F, Robino A, Rosas SE, Ruderfer D, Ruggiero D, Saba Y, Sala C, Schmidt H, Schmidt R, Scott RJ, Sedaghat S, Smith AV, Sorice R, Stengel B, Stracke S, Strauch K, Toniolo D, Uitterlinden AG, Ulivi S, Viikari JS, Völker U, Vollenweider P, Völzke H, Vuckovic D, Waldenberger M, Jin Wang J, Yang Q, Chasman DI, Tromp G, Snieder H, Heid IM, Fox CS, Köttgen A, Pattaro C, Böger CA, and Fuchsberger C

Subjects
Gene Frequency, Genome, Human, Genome-Wide Association Study, Genotyping Techniques, Humans, Polymorphism, Single Nucleotide, Computational Biology methods, Genetic Loci, Kidney physiology
Abstract

HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10 -8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples.

Published
2017
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48. Does Childhood Temperamental Activity Predict Physical Activity and Sedentary Behavior over a 30-Year Period? Evidence from the Young Finns Study.

Author

Yang X, Kaseva K, Keltikangas-Järvinen L, Pulkki-Råback L, Hirvensalo M, Jokela M, Hintsanen M, Hintsa T, Kankaanpää A, Telama R, Hutri-Kähönen N, Viikari JS, Raitakari OT, and Tammelin T

Subjects
Adolescent, Adult, Child, Child, Preschool, Female, Finland, Follow-Up Studies, Humans, Male, Mothers, Self Report, Television, Young Adult, Exercise physiology, Sedentary Behavior, Temperament physiology
Abstract

Purpose: We examined associations between childhood temperamental activity, physical activity (PA), and television (TV) viewing over a 30-year period., Method: The participants (1220 boys and 1237 girls) were aged 3, 6, 9, and 12 years in 1980 and were followed until 2011. Temperamental activity was evaluated by participants' mothers at baseline. The PA was assessed based on maternal ratings of the child from ages 3 to 6 and via self-report age from the age of 9 across all measurements. TV viewing was assessed using self-reports taken from 2001 to 2011. The associations between temperamental activity and the level and change of PA and TV viewing were determined using linear growth modeling stratified by gender and age group., Results: High temperamental activity assessed from ages 9 to 12 was associated with high levels of childhood PA in both genders, but with a steeper decline in PA levels during the first 9 years of follow-up in boys. High temperamental activity assessed from ages 3 to 6 was associated with the decline of PA from childhood to youth in girls. High childhood temperamental activity was associated with decreased levels of PA in adulthood in men, but not in women. The associations between childhood temperamental activity and TV viewing during adulthood seemed to be positive but not consistently significant in all age and gender groups., Conclusion: High temperamental activity may contribute to the development of a physically inactive lifestyle. More evidence is needed with regard to gender differences among participants in similar study settings.

Published
2017
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49. Ideal cardiovascular health in childhood-Longitudinal associations with cardiac structure and function: The Special Turku Coronary Risk Factor Intervention Project (STRIP) and the Cardiovascular Risk in Young Finns Study (YFS).

Author

Laitinen TT, Ruohonen S, Juonala M, Magnussen CG, Mikkilä V, Mikola H, Hutri-Kähönen N, Laitinen T, Tossavainen P, Jokinen E, Niinikoski H, Jula A, Viikari JS, Rönnemaa T, Raitakari OT, and Pahkala K

Subjects
Adolescent, Adult, Cardiovascular Diseases diagnosis, Cardiovascular Diseases epidemiology, Child, Female, Finland epidemiology, Follow-Up Studies, Heart Ventricles diagnostic imaging, Humans, Incidence, Male, Middle Aged, Prospective Studies, Risk Factors, Societies, Medical, Young Adult, Cardiovascular Diseases prevention & control, Echocardiography methods, Health Status, Heart Ventricles physiopathology, Risk Assessment methods, Ventricular Function, Left physiology
Abstract

Background: Ideal cardiovascular health (CVH), defined by the American Heart Association, is associated with incident cardiovascular disease in adults. However, association of the ideal CVH in childhood with current and future cardiac structure and function has not been studied., Methods and Results: The sample comprised 827 children participating in the longitudinal Special Turku Coronary Risk Factor Intervention Project (STRIP) and The Cardiovascular Risk in Young Finns Study (YFS). In STRIP, complete data on the seven ideal CVH metrics and left ventricular (LV) mass measured with echocardiography were available at the age of 15 (n=321), 17 (n=309) and 19 (n=283) years. In YFS, the cohort comprised children aged 12-18years (n=506) with complete ideal CVH metrics data from childhood and 25years later in adulthood, and echocardiography performed in adulthood. In STRIP, ideal CVH score was inversely associated with LV mass during childhood (P=0.036). In YFS, childhood ideal CVH score was inversely associated with LV mass, LV end-diastolic volume, E/e' ratio, and left atrium end-systolic volume in adulthood (all P<0.01). In addition, improvement of the ideal CVH score between childhood and adulthood was inversely associated with LV mass, LV end-diastolic volume, E/e' ratio, and left atrium end-systolic volume (all P≤0.03)., Conclusions: Childhood ideal CVH score has a long-lasting effect on cardiac structure and function, and the association is evident already in childhood. Our findings support targeting the ideal CVH metrics as part of primordial prevention of cardiovascular diseases., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Published
2017
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50. Metabolic profiling of fatty liver in young and middle-aged adults: Cross-sectional and prospective analyses of the Young Finns Study.

Author

Kaikkonen JE, Würtz P, Suomela E, Lehtovirta M, Kangas AJ, Jula A, Mikkilä V, Viikari JS, Juonala M, Rönnemaa T, Hutri-Kähönen N, Kähönen M, Lehtimäki T, Soininen P, Ala-Korpela M, and Raitakari OT

Subjects
Adult, Age Distribution, Biomarkers blood, Cardiovascular Diseases prevention & control, Cross-Sectional Studies, Fatty Acids blood, Female, Finland, Humans, Male, Metabolomics methods, Middle Aged, Non-alcoholic Fatty Liver Disease diagnostic imaging, Predictive Value of Tests, Prevalence, Prospective Studies, Risk Assessment, Sex Distribution, Ultrasonography, Doppler methods, Young Adult, Lipoproteins, HDL blood, Lipoproteins, VLDL blood, Non-alcoholic Fatty Liver Disease blood, Non-alcoholic Fatty Liver Disease epidemiology
Abstract

Nonalcoholic fatty liver is associated with obesity-related metabolic disturbances, but little is known about the metabolic perturbations preceding fatty liver disease. We performed comprehensive metabolic profiling to assess how circulating metabolites, such as lipoprotein lipids, fatty acids, amino acids, and glycolysis-related metabolites, reflect the presence of and future risk for fatty liver in young adults. Sixty-eight lipids and metabolites were quantified by nuclear magnetic resonance metabolomics in the population-based Young Finns Study from serum collected in 2001 (n = 1,575), 2007 (n = 1,509), and 2011 (n = 2,002). Fatty liver was diagnosed by ultrasound in 2011 when participants were aged 34-49 years (19% prevalence). Cross-sectional associations as well as 4-year and 10-year risks for fatty liver were assessed by logistic regression. Metabolites across multiple pathways were strongly associated with the presence of fatty liver (P < 0.0007 for 60 measures in age-adjusted and sex-adjusted cross-sectional analyses). The strongest direct associations were observed for extremely large very-low-density lipoprotein triglycerides (odds ratio [OR] = 4.86 per 1 standard deviation, 95% confidence interval 3.48-6.78), other very-low-density lipoprotein measures, and branched-chain amino acids (e.g., leucine OR = 2.94, 2.51-3.44). Strong inverse associations were observed for high-density lipoprotein measures, e.g., high-density lipoprotein size (OR = 0.36, 0.30-0.42) and several fatty acids including omega-6 (OR = 0.37, 0.32-0.42). The metabolic associations were attenuated but remained significant after adjusting for waist, physical activity, alcohol consumption, and smoking (P < 0.0007). Similar aberrations in the metabolic profile were observed already 10 years before fatty liver diagnosis., Conclusion: Circulating lipids, fatty acids, and amino acids reflect fatty liver independently of routine metabolic risk factors; these metabolic aberrations appear to precede the development of fatty liver in young adults. (Hepatology 2017;65:491-500)., (© 2016 The Authors. Hepatology published by Wiley Periodicals, Inc., on behalf of the American Association for the Study of Liver Diseases.)

Published
2017
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