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1. Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning

Author

Lahti, J, Tuominen, S, Yang, Q, Pergola, G, Ahmad, S, Amin, N, Armstrong, NJ, Beiser, A, Bey, K, Bis, JC, Boerwinkle, E, Bressler, J, Campbell, A, Campbell, H, Chen, Q, Corley, J, Cox, SR, Davies, G, De Jager, PL, Derks, EM, Faul, JD, Fitzpatrick, AL, Fohner, AE, Ford, I, Fornage, M, Gerring, Z, Grabe, HJ, Grodstein, F, Gudnason, V, Simonsick, E, Holliday, EG, Joshi, PK, Kajantie, E, Kaprio, J, Karell, P, Kleineidam, L, Knol, MJ, Kochan, NA, Kwok, JB, Leber, M, Lam, M, Lee, T, Li, S, Loukola, A, Luck, T, Marioni, RE, Mather, KA, Medland, S, Mirza, SS, Nalls, MA, Nho, K, O'Donnell, A, Oldmeadow, C, Painter, J, Pattie, A, Reppermund, S, Risacher, SL, Rose, RJ, Sadashivaiah, V, Scholz, M, Satizabal, CL, Schofield, PW, Schraut, KE, Scott, RJ, Simino, J, Smith, AV, Smith, JA, Stott, DJ, Surakka, I, Teumer, A, Thalamuthu, A, Trompet, S, Turner, ST, van der Lee, SJ, Villringer, A, Voelker, U, Wilson, RS, Wittfeld, K, Vuoksimaa, E, Xia, R, Yaffe, K, Yu, L, Zare, H, Zhao, W, Ames, D, Attia, J, Bennett, DA, Brodaty, H, Chasman, DI, Goldman, AL, Hayward, C, Ikram, MA, Jukema, JW, Kardia, SLR, Lencz, T, Loeffler, M, Mattay, VS, Palotie, A, Psaty, BM, Ramirez, A, Ridker, PM, Riedel-Heller, SG, Sachdev, PS, Saykin, AJ, Scherer, M, Schofield, PR, Sidney, S, Starr, JM, Trollor, J, Ulrich, W, Wagner, M, Weir, DR, Wilson, JF, Wright, MJ, Weinberger, DR, Debette, S, Eriksson, JG, Mosley, TH, Launer, LJ, van Duijn, CM, Deary, IJ, Seshadri, S, Raikkonen, K, Lahti, J, Tuominen, S, Yang, Q, Pergola, G, Ahmad, S, Amin, N, Armstrong, NJ, Beiser, A, Bey, K, Bis, JC, Boerwinkle, E, Bressler, J, Campbell, A, Campbell, H, Chen, Q, Corley, J, Cox, SR, Davies, G, De Jager, PL, Derks, EM, Faul, JD, Fitzpatrick, AL, Fohner, AE, Ford, I, Fornage, M, Gerring, Z, Grabe, HJ, Grodstein, F, Gudnason, V, Simonsick, E, Holliday, EG, Joshi, PK, Kajantie, E, Kaprio, J, Karell, P, Kleineidam, L, Knol, MJ, Kochan, NA, Kwok, JB, Leber, M, Lam, M, Lee, T, Li, S, Loukola, A, Luck, T, Marioni, RE, Mather, KA, Medland, S, Mirza, SS, Nalls, MA, Nho, K, O'Donnell, A, Oldmeadow, C, Painter, J, Pattie, A, Reppermund, S, Risacher, SL, Rose, RJ, Sadashivaiah, V, Scholz, M, Satizabal, CL, Schofield, PW, Schraut, KE, Scott, RJ, Simino, J, Smith, AV, Smith, JA, Stott, DJ, Surakka, I, Teumer, A, Thalamuthu, A, Trompet, S, Turner, ST, van der Lee, SJ, Villringer, A, Voelker, U, Wilson, RS, Wittfeld, K, Vuoksimaa, E, Xia, R, Yaffe, K, Yu, L, Zare, H, Zhao, W, Ames, D, Attia, J, Bennett, DA, Brodaty, H, Chasman, DI, Goldman, AL, Hayward, C, Ikram, MA, Jukema, JW, Kardia, SLR, Lencz, T, Loeffler, M, Mattay, VS, Palotie, A, Psaty, BM, Ramirez, A, Ridker, PM, Riedel-Heller, SG, Sachdev, PS, Saykin, AJ, Scherer, M, Schofield, PR, Sidney, S, Starr, JM, Trollor, J, Ulrich, W, Wagner, M, Weir, DR, Wilson, JF, Wright, MJ, Weinberger, DR, Debette, S, Eriksson, JG, Mosley, TH, Launer, LJ, van Duijn, CM, Deary, IJ, Seshadri, S, and Raikkonen, K

Abstract

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.

Published
2022

2. Genetic insights into biological mechanisms governing human ovarian ageing

Author

Ruth, KS, Day, FR, Hussain, J, Martinez-Marchal, A, Aiken, CE, Azad, A, Thompson, DJ, Knoblochova, L, Abe, H, Tarry-Adkins, JL, Gonzalez, JM, Fontanillas, P, Claringbould, A, Bakker, OB, Sulem, P, Walters, RG, Terao, C, Turon, S, Horikoshi, M, Lin, K, Onland-Moret, NC, Sankar, A, Hertz, EPT, Timshel, PN, Shukla, V, Borup, R, Olsen, KW, Aguilera, P, Ferrer-Roda, M, Huang, Y, Stankovic, S, Timmers, PRHJ, Ahearn, TU, Alizadeh, BZ, Naderi, E, Andrulis, IL, Arnold, AM, Aronson, KJ, Augustinsson, A, Bandinelli, S, Barbieri, CM, Beaumont, RN, Becher, H, Beckmann, MW, Benonisdottir, S, Bergmann, S, Bochud, M, Boerwinkle, E, Bojesen, SE, Bolla, MK, Boomsma, DI, Bowker, N, Brody, JA, Broer, L, Buring, JE, Campbell, A, Campbell, H, Castelao, JE, Catamo, E, Chanock, SJ, Chenevix-Trench, G, Ciullo, M, Corre, T, Couch, FJ, Cox, A, Crisponi, L, Cross, SS, Cucca, F, Czene, K, Smith, GD, de Geus, EJCN, de Mutsert, R, De Vivo, I, Demerath, EW, Dennis, J, Dunning, AM, Dwek, M, Eriksson, M, Esko, T, Fasching, PA, Faul, JD, Ferrucci, L, Franceschini, N, Frayling, TM, Gago-Dominguez, M, Mezzavilla, M, Garcia-Closas, M, Gieger, C, Giles, GG, Grallert, H, Gudbjartsson, DF, Gudnason, V, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hayward, C, He, C, He, W, Heiss, G, Hoffding, MK, Hopper, JL, Hottenga, JJ, Hu, F, Hunter, D, Ikram, MA, Jackson, RD, Joaquim, MDR, John, EM, Joshi, PK, Karasik, D, Kardia, SLR, Kartsonaki, C, Karlsson, R, Kitahara, CM, Kolcic, I, Kooperberg, C, Kraft, P, Kurian, AW, Kutalik, Z, La Bianca, M, LaChance, G, Langenberg, C, Launer, LJ, Laven, JSE, Lawlor, DA, Le Marchand, L, Li, J, Lindblom, A, Lindstrom, S, Lindstrom, T, Linet, M, Liu, Y, Liu, S, Luan, J, Magi, R, Magnusson, PKE, Mangino, M, Mannermaa, A, Marco, B, Marten, J, Martin, NG, Mbarek, H, McKnight, B, Medland, SE, Meisinger, C, Meitinger, T, Menni, C, Metspalu, A, Milani, L, Milne, RL, Montgomery, GW, Mook-Kanamori, DO, Mulas, A, Mulligan, AM, Murray, A, Nalls, MA, Newman, A, Noordam, R, Nutile, T, Nyholt, DR, Olshan, AF, Olsson, H, Painter, JN, Patel, AV, Pedersen, NL, Perjakova, N, Peters, A, Peters, U, Pharoah, PDP, Polasek, O, Porcu, E, Psaty, BM, Rahman, I, Rennert, G, Rennert, HS, Ridker, PM, Ring, SM, Robino, A, Rose, LM, Rosendaal, FR, Rossouw, J, Rudan, I, Rueedi, R, Ruggiero, D, Sala, CF, Saloustros, E, Sandler, DP, Sanna, S, Sawyer, EJ, Sarnowski, C, Schlessinger, D, Schmidt, MK, Schoemaker, MJ, Schraut, KE, Scott, C, Shekari, S, Shrikhande, A, Smith, AV, Smith, BH, Smith, JA, Sorice, R, Southey, MC, Spector, TD, Spinelli, JJ, Stampfer, M, Stoeckl, D, van Meurs, JBJ, Strauch, K, Styrkarsdottir, U, Swerdlow, AJ, Tanaka, T, Teras, LR, Teumer, A, thorsteinsdottir, U, Timpson, NJ, Toniolo, D, Traglia, M, Troester, MA, Truong, T, Tyrrell, J, Uitterlinden, AG, Ulivi, S, Vachon, CM, Vitart, V, Voelker, U, Vollenweider, P, Voelzke, H, Wang, Q, Wareham, NJ, Weinberg, CR, Weir, DR, Wilcox, AN, van Dijk, KW, Willemsen, G, Wilson, JF, Wolffenbuttel, BHR, Wolk, A, Wood, AR, Zhao, W, Zygmunt, M, Chen, Z, Li, L, Franke, L, Burgess, S, Deelen, P, Pers, TH, Grondahl, ML, Andersen, CY, Pujol, A, Lopez-Contreras, AJ, Daniel, JA, Stefansson, K, Chang-Claude, J, van der Schouw, YT, Lunetta, KL, Chasman, DI, Easton, DF, Visser, JA, Ozanne, SE, Namekawa, SH, Solc, P, Murabito, JM, Ong, KK, Hoffmann, ER, Roig, I, Perry, JRB, Ruth, KS, Day, FR, Hussain, J, Martinez-Marchal, A, Aiken, CE, Azad, A, Thompson, DJ, Knoblochova, L, Abe, H, Tarry-Adkins, JL, Gonzalez, JM, Fontanillas, P, Claringbould, A, Bakker, OB, Sulem, P, Walters, RG, Terao, C, Turon, S, Horikoshi, M, Lin, K, Onland-Moret, NC, Sankar, A, Hertz, EPT, Timshel, PN, Shukla, V, Borup, R, Olsen, KW, Aguilera, P, Ferrer-Roda, M, Huang, Y, Stankovic, S, Timmers, PRHJ, Ahearn, TU, Alizadeh, BZ, Naderi, E, Andrulis, IL, Arnold, AM, Aronson, KJ, Augustinsson, A, Bandinelli, S, Barbieri, CM, Beaumont, RN, Becher, H, Beckmann, MW, Benonisdottir, S, Bergmann, S, Bochud, M, Boerwinkle, E, Bojesen, SE, Bolla, MK, Boomsma, DI, Bowker, N, Brody, JA, Broer, L, Buring, JE, Campbell, A, Campbell, H, Castelao, JE, Catamo, E, Chanock, SJ, Chenevix-Trench, G, Ciullo, M, Corre, T, Couch, FJ, Cox, A, Crisponi, L, Cross, SS, Cucca, F, Czene, K, Smith, GD, de Geus, EJCN, de Mutsert, R, De Vivo, I, Demerath, EW, Dennis, J, Dunning, AM, Dwek, M, Eriksson, M, Esko, T, Fasching, PA, Faul, JD, Ferrucci, L, Franceschini, N, Frayling, TM, Gago-Dominguez, M, Mezzavilla, M, Garcia-Closas, M, Gieger, C, Giles, GG, Grallert, H, Gudbjartsson, DF, Gudnason, V, Guenel, P, Haiman, CA, Hakansson, N, Hall, P, Hayward, C, He, C, He, W, Heiss, G, Hoffding, MK, Hopper, JL, Hottenga, JJ, Hu, F, Hunter, D, Ikram, MA, Jackson, RD, Joaquim, MDR, John, EM, Joshi, PK, Karasik, D, Kardia, SLR, Kartsonaki, C, Karlsson, R, Kitahara, CM, Kolcic, I, Kooperberg, C, Kraft, P, Kurian, AW, Kutalik, Z, La Bianca, M, LaChance, G, Langenberg, C, Launer, LJ, Laven, JSE, Lawlor, DA, Le Marchand, L, Li, J, Lindblom, A, Lindstrom, S, Lindstrom, T, Linet, M, Liu, Y, Liu, S, Luan, J, Magi, R, Magnusson, PKE, Mangino, M, Mannermaa, A, Marco, B, Marten, J, Martin, NG, Mbarek, H, McKnight, B, Medland, SE, Meisinger, C, Meitinger, T, Menni, C, Metspalu, A, Milani, L, Milne, RL, Montgomery, GW, Mook-Kanamori, DO, Mulas, A, Mulligan, AM, Murray, A, Nalls, MA, Newman, A, Noordam, R, Nutile, T, Nyholt, DR, Olshan, AF, Olsson, H, Painter, JN, Patel, AV, Pedersen, NL, Perjakova, N, Peters, A, Peters, U, Pharoah, PDP, Polasek, O, Porcu, E, Psaty, BM, Rahman, I, Rennert, G, Rennert, HS, Ridker, PM, Ring, SM, Robino, A, Rose, LM, Rosendaal, FR, Rossouw, J, Rudan, I, Rueedi, R, Ruggiero, D, Sala, CF, Saloustros, E, Sandler, DP, Sanna, S, Sawyer, EJ, Sarnowski, C, Schlessinger, D, Schmidt, MK, Schoemaker, MJ, Schraut, KE, Scott, C, Shekari, S, Shrikhande, A, Smith, AV, Smith, BH, Smith, JA, Sorice, R, Southey, MC, Spector, TD, Spinelli, JJ, Stampfer, M, Stoeckl, D, van Meurs, JBJ, Strauch, K, Styrkarsdottir, U, Swerdlow, AJ, Tanaka, T, Teras, LR, Teumer, A, thorsteinsdottir, U, Timpson, NJ, Toniolo, D, Traglia, M, Troester, MA, Truong, T, Tyrrell, J, Uitterlinden, AG, Ulivi, S, Vachon, CM, Vitart, V, Voelker, U, Vollenweider, P, Voelzke, H, Wang, Q, Wareham, NJ, Weinberg, CR, Weir, DR, Wilcox, AN, van Dijk, KW, Willemsen, G, Wilson, JF, Wolffenbuttel, BHR, Wolk, A, Wood, AR, Zhao, W, Zygmunt, M, Chen, Z, Li, L, Franke, L, Burgess, S, Deelen, P, Pers, TH, Grondahl, ML, Andersen, CY, Pujol, A, Lopez-Contreras, AJ, Daniel, JA, Stefansson, K, Chang-Claude, J, van der Schouw, YT, Lunetta, KL, Chasman, DI, Easton, DF, Visser, JA, Ozanne, SE, Namekawa, SH, Solc, P, Murabito, JM, Ong, KK, Hoffmann, ER, Roig, I, and Perry, JRB

Abstract

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

Published
2021

3. Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity

Author

Joshi, PK, Pirastu, N, Kentistou, KA, Fischer, K, Hofer, E, Schraut, KE, Clark, DW, Nutile, T, Barnes, CLK, Timmers, P, Shen, X, Gandin, I, McDaid, AF, Hansen, TF, Gordon, SD, Giulianini, F, Boutin, TS, Abdellaoui, A, Zhao, W, Medina-Gomez, C, Bartz, TM, Trompet, S, Lange, LA, Raffield, L, van der Spek, Ashley, Galesloot, TE, Proitsi, P, Yanek, LR, Bielak, LF, Payton, A, Murgia, F, Concas, MP, Biino, G, Tajuddin, S M, Seppala, I, Amin, Najaf, Boerwinkle, E, Borglum, AD, Campbell, A (Archie), Demerath, EW, Demuth, I, Faul, JD, Ford, I, Gialluisi, A, Gogele, M, Graff, M, Hingorani, A, Hottenga, JJ, Hougaard, DM, Hurme, MA, Ikram, Arfan, Jylha, M, Kuh, D, Ligthart, L, Lill, CM, Lindenberger, U, Lumley, T, Magi, R, Marques-Vidal, P, Medland, SE, Milani, L, Nagy, R, Ollier, WER, Peyser, PA, Pramstaller, PP, Ridker, PM, Rivadeneira, F, Ruggiero, D, Saba, Y, Schmidt, R, Schmidt, H, Slagboom, PE (Eline), Smith, BH, Smith, JA, Sotoodehnia, N, Steinhagen-Thiessen, E, van Rooij, FJA, Verbeek, AL, Vermeulen, SH, Vollenweider, P, Wang, YP, Werge, T, Whitfield, JB, Zonderman, AB, Lehtimaki, T, Evans, MK, Pirastu, M, Fuchsberger, C, Bertram, L, Pendleton, N, Kardia, SLR, Ciullo, M, Becker, DM, Wong, A, Psaty, BM, Duijn, Cornelia, Wilson, JG, Jukema, JW, Kiemeney, L, Uitterlinden, André, Franceschini, N, North, KE, Weir, DR, Metspalu, A, Boomsma, DI, Hayward, C, Chasman, D, Martin, NG, Sattar, N, Campbell, H, Esko, T, Kutalik, Z, Wilson, JF, Joshi, PK, Pirastu, N, Kentistou, KA, Fischer, K, Hofer, E, Schraut, KE, Clark, DW, Nutile, T, Barnes, CLK, Timmers, P, Shen, X, Gandin, I, McDaid, AF, Hansen, TF, Gordon, SD, Giulianini, F, Boutin, TS, Abdellaoui, A, Zhao, W, Medina-Gomez, C, Bartz, TM, Trompet, S, Lange, LA, Raffield, L, van der Spek, Ashley, Galesloot, TE, Proitsi, P, Yanek, LR, Bielak, LF, Payton, A, Murgia, F, Concas, MP, Biino, G, Tajuddin, S M, Seppala, I, Amin, Najaf, Boerwinkle, E, Borglum, AD, Campbell, A (Archie), Demerath, EW, Demuth, I, Faul, JD, Ford, I, Gialluisi, A, Gogele, M, Graff, M, Hingorani, A, Hottenga, JJ, Hougaard, DM, Hurme, MA, Ikram, Arfan, Jylha, M, Kuh, D, Ligthart, L, Lill, CM, Lindenberger, U, Lumley, T, Magi, R, Marques-Vidal, P, Medland, SE, Milani, L, Nagy, R, Ollier, WER, Peyser, PA, Pramstaller, PP, Ridker, PM, Rivadeneira, F, Ruggiero, D, Saba, Y, Schmidt, R, Schmidt, H, Slagboom, PE (Eline), Smith, BH, Smith, JA, Sotoodehnia, N, Steinhagen-Thiessen, E, van Rooij, FJA, Verbeek, AL, Vermeulen, SH, Vollenweider, P, Wang, YP, Werge, T, Whitfield, JB, Zonderman, AB, Lehtimaki, T, Evans, MK, Pirastu, M, Fuchsberger, C, Bertram, L, Pendleton, N, Kardia, SLR, Ciullo, M, Becker, DM, Wong, A, Psaty, BM, Duijn, Cornelia, Wilson, JG, Jukema, JW, Kiemeney, L, Uitterlinden, André, Franceschini, N, North, KE, Weir, DR, Metspalu, A, Boomsma, DI, Hayward, C, Chasman, D, Martin, NG, Sattar, N, Campbell, H, Esko, T, Kutalik, Z, and Wilson, JF

Published
2017

4. Genome-wide association study identifies 74 loci associated with educational attainment

Author

Okbay, Aysu, Beauchamp, JP, Fontana, MA, Lee, JJ, Pers, TH, Rietveld, Niels, Turley, P, Chen, GB, Emilsson, V, Meddens, SFW, Oskarsson, S, Pickrell, JK, Thom, K, Timshel, P, Vlaming, Ronald, Abdellaoui, A, Ahluwalia, TS, Bacelis, J, Baumbach, C, Bjornsdottir, G, Brandsma, Johan, Concas, MP, Derringer, J, Furlotte, NA, Galesloot, TE, Girotto, G, Gupta, R, Hall, LM, Harris, SE, Hofer, E, Horikoshi, M, Huffman, JE, Kaasik, K, Kalafati, IP, Karlsson, R, Kong, A, Lahti, J, van der Lee, Sven, de Leeuw, C, Lind, PA, Lindgren, KO, Liu, T, Mangino, M, Marten, J, Mihailov, E, Miller, MB, van der Most, PJ, Oldmeadow, C, Payton, A, Pervjakova, N, Peyrot, WJ, Qian, Y, Raitakari, O, Rueedi, R, Salvi, E, Schmidt, B, Schraut, KE, Shi, JX, Smith, AV, Poot, Raymond, St Pourcain, B, Teumer, A, Thorleifsson, G, Verweij, N (Niek), Vuckovic, D, Wellmann, J, Westra, HJ, Yang, JY, Zhao, W, Zhu, ZH, Alizadeh, BZ, Amin, Najaf, Bakshi, A, Baumeister, SE, Biino, G, Bonnelykke, K, Boyle, PA, Campbell, H, Cappuccio, FP, Davies, G, De Neve, JE, Deloukas, P, Demuth, I, Ding, J, Eibich, P, Eisele, L, Eklund, N, Evans, DM, Faul, JD, Feitosa, MF, Forstner, AJ, Gandin, I, Gunnarsson, B, Halldorsson, BV, Harris, TB, Heath, AC, Hocking, LJ, Holliday, EG, Homuth, G, Horan, MA, Hottenga, JJ, De Jager, PL, Joshi, PK, Jugessur, A, Kaakinen, MA, Kahonen, M, Kanoni, S, Keltigangas-Jarvinen, L, Kiemeney, LALM, Kolcic, I, Koskinen, S, Kraja, AT, Kroh, M, Kutalik, Z, Latvala, A, Launer, LJ, Lebreton, MP, Levinson, DF, Lichtenstein, P, Lichtner, P, Liewald, DCM, Loukola, A, Madden, PA, Magi, R, Maki-Opas, T, Marioni, RE, Marques-Vidal, P, Meddens, GA, McMahon, G, Meisinger, C, Meitinger, T, Milaneschi, Y, Milani, L, Montgomery, GW, Myhre, R, Nelson, CP, Nyholt, DR, Ollier, WER, Palotie, A, Paternoster, L, Pedersen, NL, Petrovic, KE, Porteous, DJ, Raikkonen, K, Ring, SM, Robino, A, Rostapshova, O, Rudan, I, Rustichini, A, Salomaa, V, Sanders, AR, Sarin, AP, Schmidt, Heléna, Scott, RJ, Smith, BH, Smith, JA, Staessen, JA, Steinhagen-Thiessen, E, Strauch, K, Terracciano, A, Tobin, MD, Ulivi, S, Vaccargiu, S, Quaye, L, van Rooij, FJA, Venturini, C, Vinkhuyzen, AAE, Volker, U, Volzke, H, Vonk, JM, Vozzi, D, Waage, J, Ware, EB, Willemsen, G, Attia, JR, Bennett, DA, Berger, K, Bertram, L, Bisgaard, H, Boomsma, DI, Borecki, IB, Bultmann, U, Chabris, CF, Cucca, F, Cusi, D, Deary, IJ, Dedoussis, GV, Duijn, Cornelia, Eriksson, JG, Franke, B, Franke, L, Gasparini, P, Gejman, PV, Gieger, C, Grabe, HJ, Gratten, J, Groenen, Patrick, Gudnason, V, van der Harst, P, Hayward, C, Hinds, DA, Hoffmann, W, Hyppnen, E, Iacono, WG, Jacobsson, B, Jarvelin, MR, Jockel, KH, Kaprio, J, Kardia, SLR, Lehtimaki, T, Lehrer, SF, Magnusson, PKE, Martin, NG, McGue, M, Metspalu, A, Pendleton, N, Penninx, BWJH, Perola, M, Pirastu, N, Pirastu, M, Polasek, O, Posthuma, Daniëlle, Power, C, Province, MA, Samani, NJ, Schlessinger, D, Schmidt, R, Sorensen, TIA, Spector, TD, Stefansson, K, Thorsteinsdottir, U, Thurik, Roy, Timpson, NJ, Tiemeier, Henning, Tung, JY, Uitterlinden, André, Vitart, V, Vollenweider, P, Weir, DR, Wilson, JF, Wright, AF, Conley, DC, Krueger, RF, Smith, GD, Hofman, Bert, Laibson, DI, Medland, SE, Meyer, MN, Yang, Jiaqi, Johannesson, M, Visscher, PM, Esko, T, Koellinger, PD, Cesarini, D, Benjamin, DJ, Okbay, Aysu, Beauchamp, JP, Fontana, MA, Lee, JJ, Pers, TH, Rietveld, Niels, Turley, P, Chen, GB, Emilsson, V, Meddens, SFW, Oskarsson, S, Pickrell, JK, Thom, K, Timshel, P, Vlaming, Ronald, Abdellaoui, A, Ahluwalia, TS, Bacelis, J, Baumbach, C, Bjornsdottir, G, Brandsma, Johan, Concas, MP, Derringer, J, Furlotte, NA, Galesloot, TE, Girotto, G, Gupta, R, Hall, LM, Harris, SE, Hofer, E, Horikoshi, M, Huffman, JE, Kaasik, K, Kalafati, IP, Karlsson, R, Kong, A, Lahti, J, van der Lee, Sven, de Leeuw, C, Lind, PA, Lindgren, KO, Liu, T, Mangino, M, Marten, J, Mihailov, E, Miller, MB, van der Most, PJ, Oldmeadow, C, Payton, A, Pervjakova, N, Peyrot, WJ, Qian, Y, Raitakari, O, Rueedi, R, Salvi, E, Schmidt, B, Schraut, KE, Shi, JX, Smith, AV, Poot, Raymond, St Pourcain, B, Teumer, A, Thorleifsson, G, Verweij, N (Niek), Vuckovic, D, Wellmann, J, Westra, HJ, Yang, JY, Zhao, W, Zhu, ZH, Alizadeh, BZ, Amin, Najaf, Bakshi, A, Baumeister, SE, Biino, G, Bonnelykke, K, Boyle, PA, Campbell, H, Cappuccio, FP, Davies, G, De Neve, JE, Deloukas, P, Demuth, I, Ding, J, Eibich, P, Eisele, L, Eklund, N, Evans, DM, Faul, JD, Feitosa, MF, Forstner, AJ, Gandin, I, Gunnarsson, B, Halldorsson, BV, Harris, TB, Heath, AC, Hocking, LJ, Holliday, EG, Homuth, G, Horan, MA, Hottenga, JJ, De Jager, PL, Joshi, PK, Jugessur, A, Kaakinen, MA, Kahonen, M, Kanoni, S, Keltigangas-Jarvinen, L, Kiemeney, LALM, Kolcic, I, Koskinen, S, Kraja, AT, Kroh, M, Kutalik, Z, Latvala, A, Launer, LJ, Lebreton, MP, Levinson, DF, Lichtenstein, P, Lichtner, P, Liewald, DCM, Loukola, A, Madden, PA, Magi, R, Maki-Opas, T, Marioni, RE, Marques-Vidal, P, Meddens, GA, McMahon, G, Meisinger, C, Meitinger, T, Milaneschi, Y, Milani, L, Montgomery, GW, Myhre, R, Nelson, CP, Nyholt, DR, Ollier, WER, Palotie, A, Paternoster, L, Pedersen, NL, Petrovic, KE, Porteous, DJ, Raikkonen, K, Ring, SM, Robino, A, Rostapshova, O, Rudan, I, Rustichini, A, Salomaa, V, Sanders, AR, Sarin, AP, Schmidt, Heléna, Scott, RJ, Smith, BH, Smith, JA, Staessen, JA, Steinhagen-Thiessen, E, Strauch, K, Terracciano, A, Tobin, MD, Ulivi, S, Vaccargiu, S, Quaye, L, van Rooij, FJA, Venturini, C, Vinkhuyzen, AAE, Volker, U, Volzke, H, Vonk, JM, Vozzi, D, Waage, J, Ware, EB, Willemsen, G, Attia, JR, Bennett, DA, Berger, K, Bertram, L, Bisgaard, H, Boomsma, DI, Borecki, IB, Bultmann, U, Chabris, CF, Cucca, F, Cusi, D, Deary, IJ, Dedoussis, GV, Duijn, Cornelia, Eriksson, JG, Franke, B, Franke, L, Gasparini, P, Gejman, PV, Gieger, C, Grabe, HJ, Gratten, J, Groenen, Patrick, Gudnason, V, van der Harst, P, Hayward, C, Hinds, DA, Hoffmann, W, Hyppnen, E, Iacono, WG, Jacobsson, B, Jarvelin, MR, Jockel, KH, Kaprio, J, Kardia, SLR, Lehtimaki, T, Lehrer, SF, Magnusson, PKE, Martin, NG, McGue, M, Metspalu, A, Pendleton, N, Penninx, BWJH, Perola, M, Pirastu, N, Pirastu, M, Polasek, O, Posthuma, Daniëlle, Power, C, Province, MA, Samani, NJ, Schlessinger, D, Schmidt, R, Sorensen, TIA, Spector, TD, Stefansson, K, Thorsteinsdottir, U, Thurik, Roy, Timpson, NJ, Tiemeier, Henning, Tung, JY, Uitterlinden, André, Vitart, V, Vollenweider, P, Weir, DR, Wilson, JF, Wright, AF, Conley, DC, Krueger, RF, Smith, GD, Hofman, Bert, Laibson, DI, Medland, SE, Meyer, MN, Yang, Jiaqi, Johannesson, M, Visscher, PM, Esko, T, Koellinger, PD, Cesarini, D, and Benjamin, DJ

Abstract

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals(1). Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample(1,2) of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Published
2016

5. Genetic variants linked to education predict longevity

Author

Chris Power, Gail Davies, Ilaria Gandin, Panagiotis Deloukas, Jennifer E. Huffman, Pascal Timshel, Albert V. Smith, A. Kong, Paul Lichtenstein, Joseph K. Pickrell, Philipp Koellinger, P. L. De Jager, Reedik Mägi, G. B. Chen, Neil Pendleton, B. V. Halldórsson, George Dedoussis, Antti-Pekka Sarin, Natalia Pervjakova, Veikko Salomaa, Simona Vaccargiu, Ozren Polasek, K. H. Jöckel, Elisabeth Steinhagen-Thiessen, Y. Milaneschi, Jessica D. Faul, Patricia A. Boyle, Patrik K. E. Magnusson, Igor Rudan, Christopher P. Nelson, Vilmundur Gudnason, John Attia, Jürgen Wellmann, Kristi Läll, Konstantin Strauch, Stuart J. Ritchie, Markus Perola, Nicola Pirastu, Klaus Bønnelykke, Robert Karlsson, R. de Vlaming, Liisa Keltigangas-Jarvinen, Thomas Meitinger, Riccardo E. Marioni, Anu Loukola, Barbera Franke, Reinhold Schmidt, Maël Lebreton, Sven Oskarsson, E. Mihailov, Harm-Jan Westra, David R. Weir, Aldi T. Kraja, Niek Verweij, Peter M. Visscher, Hans-Jörgen Grabe, Johannes H. Brandsma, Mark Adams, R. J. Scott, G. Thorleifsson, Tõnu Esko, Mika Kähönen, Saskia P. Hagenaars, Patrick Turley, Johannes Waage, Peter Lichtner, Dragana Vuckovic, Antonietta Robino, Henry Völzke, Lydia Quaye, C. de Leeuw, Marika Kaakinen, Wei Zhao, Abdel Abdellaoui, Reka Nagy, Pedro Marques-Vidal, Johan G. Eriksson, Alan F. Wright, Andres Metspalu, Lavinia Paternoster, Momoko Horikoshi, Jan A. Staessen, Tarunveer S. Ahluwalia, Tian Liu, Martin Kroh, Aldo Rustichini, Giorgia Girotto, Cristina Venturini, Lili Milani, Jennifer A. Smith, Ginevra Biino, Tessel E. Galesloot, Michael A. Horan, Gerardus A. Meddens, James F. Wilson, Francesco Cucca, Peter Vollenweider, Erika Salvi, P. J. van der Most, Jari Lahti, Campbell A, David Laibson, Andrew Bakshi, Wolfgang Hoffmann, Tomi Mäki-Opas, Andreas J. Forstner, C M van Duijn, Nicholas G. Martin, Jonathan Marten, Ute Bültmann, Olli T. Raitakari, David A. Bennett, A.G. Uitterlinden, J. E. De Neve, Ingrid B. Borecki, WD Hill, Bo Jacobsson, Antti Latvala, Katri Räikkönen, Michael B. Miller, Jonathan P. Beauchamp, S. J. van der Lee, Ilja Demuth, Stavroula Kanoni, Veronique Vitart, Elina Hyppönen, N. Eklund, Francesco P. Cappuccio, Robert F. Krueger, Maria Pina Concas, Jaime Derringer, F. J.A. Van Rooij, Helena Schmidt, Patrick J. F. Groenen, Valur Emilsson, Rico Rueedi, Aysu Okbay, Georg Homuth, Edith Hofer, W. E. R. Ollier, Hannah Campbell, Paolo Gasparini, Mark Alan Fontana, Magnus Johannesson, Seppo Koskinen, Christopher F. Chabris, Jouke-Jan Hottenga, Christine Meisinger, Kari Stefansson, Jun Ding, Tia Sorensen, Brenda W.J.H. Penninx, Michelle N. Meyer, James J. Lee, Diego Vozzi, Gonneke Willemsen, K. Petrovic, Sarah E. Medland, Mary F. Feitosa, Henning Tiemeier, L. J. Launer, William G. Iacono, Massimo Mangino, Tune H. Pers, S. E. Baumeister, Christopher Oldmeadow, Grant W. Montgomery, Marjo-Riitta Järvelin, Jaakko Kaprio, Catharine R. Gale, S.F.W. Meddens, Kevin Thom, Klaus Berger, Pablo V. Gejman, Lude Franke, Gyda Bjornsdottir, Daniel J. Benjamin, Steven F. Lehrer, Krista Fischer, Alan R. Sanders, S. Ulivi, Katharina E. Schraut, Tim D. Spector, Amy Hofman, Matt McGue, Terho Lehtimäki, D. C. Liewald, Hans Bisgaard, L. Eisele, Astanand Jugessur, George Davey Smith, T.B. Harris, A.R. Thurik, Cornelius A. Rietveld, David Schlessinger, Z. Kutalik, David J. Porteous, Lynne J. Hocking, N J Timpson, A. Palotie, Lambertus A. Kiemeney, Ian J. Deary, Sharon L.R. Kardia, Peter K. Joshi, Nilesh J. Samani, Michael A. Province, Börge Schmidt, Richa Gupta, Carmen Amador, Erin B. Ware, Joyce Y. Tung, Ioanna-Panagiota Kalafati, Lars Bertram, Caroline Hayward, P. van der Harst, Penelope A. Lind, Kadri Kaasik, N.A. Furlotte, Sarah E. Harris, B. St Pourcain, Susan M. Ring, Zhihong Zhu, Alexander Teumer, Behrooz Z. Alizadeh, Judith M. Vonk, Blair H. Smith, A Payton, Wouter J. Peyrot, Jacob Gratten, Douglas F. Levinson, C Gieger, Leanne M. Hall, Andrew Heath, Mario Pirastu, Peter Eibich, Nancy L. Pedersen, Ronny Myhre, Antonio Terracciano, David M. Evans, Raymond A. Poot, Uwe Völker, Dorret I. Boomsma, Clemens Baumbach, Unnur Thorsteinsdottir, Ivana Kolcic, Jia-Shu Yang, Dalton Conley, A. A. Vinkhuyzen, Danielle Posthuma, Karl-Oskar Lindgren, Olga Rostapshova, Jonas Bacelis, Daniele Cusi, Yong Qian, Bjarni Gunnarsson, George McMahon, Elizabeth G. Holliday, Pamela A. F. Madden, David A. Hinds, David Cesarini, Jianxin Shi, Najaf Amin, Dale R. Nyholt, Applied Economics, Epidemiology, Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Research Institute for Asthma and COPD (GRIAC), Aletta Jacobs School of Public Health, Public Health Research (PHR), Stem Cell Aging Leukemia and Lymphoma (SALL), Cardiovascular Centre (CVC), Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, EMGO - Mental health, Complex Trait Genetics, Biological Psychology, Marioni, RE, Ritchie, SJ, Joshi, PK, Hagenaars, SP, Hypponen, E, Benjamin, DJ, Social Science Genetic Association Consortium, Marioni, Re, Ritchie, Sj, Joshi, Pk, Hagenaars, Sp, Okbay, A, Fischer, K, Adams, Mj, Hill, Wd, Davies, G, Nagy, R, Amador, C, Läll, K, Metspalu, A, Liewald, Dc, Campbell, A, Wilson, Jf, Hayward, C, Esko, T, Porteous, Dj, Gale, Cr, Deary, Ij, Beauchamp, Jp, Fontana, Ma, Lee, Jj, Pers, Th, Rietveld, Ca, Turley, P, Chen, Gb, Emilsson, V, Meddens, Sf, Oskarsson, S, Pickrell, Jk, Thom, K, Timshel, P, de Vlaming, R, Abdellaoui, A, Ahluwalia, T, Bacelis, J, Baumbach, C, Bjornsdottir, G, Brandsma, Jh, Concas, MARIA PINA, Derringer, J, Furlotte, Na, Galesloot, Te, Girotto, Giorgia, Gupta, R, Hall, Lm, Harris, Se, Hofer, E, Horikoshi, M, Huffman, Je, Kaasik, K, Kalafati, Ip, Karlsson, R, Kong, A, Lahti, J, van der Lee, Sj, de Leeuw, C, Lind, Pa, Lindgren, Ko, Liu, T, Mangino, M, Marten, J, Mihailov, E, Miller, Mb, van der Most, Pj, Oldmeadow, C, Payton, A, Pervjakova, N, Peyrot, Wj, Qian, Y, Raitakari, O, Rueedi, R, Salvi, E, Schmidt, B, Schraut, Ke, Shi, J, Smith, Av, Poot, Ra, St Pourcain, B, Teumer, A, Thorleifsson, G, Verweij, N, Vuckovic, Dragana, Wellmann, J, Westra, Hj, Yang, J, Zhao, W, Zhu, Z, Alizadeh, Bz, Amin, N, Bakshi, A, Baumeister, Se, Biino, G, Bønnelykke, K, Boyle, Pa, Campbell, H, Cappuccio, Fp, De Neve, Je, Deloukas, P, Demuth, I, Ding, J, Eibich, P, Eisele, L, Eklund, N, Evans, Dm, Faul, Jd, Feitosa, Mf, Forstner, Aj, Gandin, Ilaria, Gunnarsson, B, Halldórsson, Bv, Harris, Tb, Heath, Ac, Hocking, Lj, Holliday, Eg, Homuth, G, Horan, Ma, Hottenga, Jj, de Jager, Pl, Jugessur, A, Kaakinen, Ma, Kähönen, M, Kanoni, S, Keltigangas Järvinen, L, Kiemeney, La, Kolcic, I, Koskinen, S, Kraja, At, Kroh, M, Kutalik, Z, Latvala, A, Launer, Lj, Lebreton, Mp, Levinson, Df, Lichtenstein, P, Lichtner, P, Loukola, A, Madden, Pa, Mägi, R, Mäki Opas, T, Marques Vidal, P, Meddens, Ga, Mcmahon, G, Meisinger, C, Meitinger, T, Milaneschi, Y, Milani, L, Montgomery, Gw, Myhre, R, Nelson, Cp, Nyholt, Dr, Ollier, We, Palotie, A, Paternoster, L, Pedersen, Nl, Petrovic, Ke, Räikkönen, K, Ring, Sm, Robino, Antonietta, Rostapshova, O, Rudan, I, Rustichini, A, Salomaa, V, Sanders, Ar, Sarin, Ap, Schmidt, H, Scott, Rj, Smith, Bh, Smith, Ja, Staessen, Ja, Steinhagen Thiessen, E, Strauch, K, Terracciano, A, Tobin, Md, Ulivi, Sheila, Vaccargiu, S, Quaye, L, van Rooij, Fj, Venturini, C, Vinkhuyzen, Aa, Völker, U, Völzke, H, Vonk, Jm, Vozzi, Diego, Waage, J, Ware, Eb, Willemsen, G, Attia, Jr, Bennett, Da, Berger, K, Bertram, L, Bisgaard, H, Boomsma, Di, Borecki, Ib, Bultmann, U, Chabris, Cf, Cucca, F, Cusi, D, Dedoussis, Gv, van Duijn, Cm, Eriksson, Jg, Franke, B, Franke, L, Gasparini, Paolo, Gejman, Pv, Gieger, C, Grabe, Hj, Gratten, J, Groenen, Pj, Gudnason, V, van der Harst, P, Hinds, Da, Hoffmann, W, Iacono, Wg, Jacobsson, B, Järvelin, Mr, Jöckel, Kh, Kaprio, J, Kardia, Sl, Lehtimäki, T, Lehrer, Sf, Magnusson, Pk, Martin, Ng, Mcgue, M, Pendleton, N, Penninx, Bw, Perola, M, Pirastu, Nicola, Pirastu, M, Polasek, O, Posthuma, D, Power, C, Province, Ma, Samani, Nj, Schlessinger, D, Schmidt, R, Sørensen, Ti, Spector, Td, Stefansson, K, Thorsteinsdottir, U, Thurik, Ar, Timpson, Nj, Tiemeier, H, Tung, Jy, Uitterlinden, Ag, Vitart, V, Vollenweider, P, Weir, Dr, Wright, Af, Conley, Dc, Krueger, Rf, Smith, Gd, Hofman, A, Laibson, Di, Medland, Se, Meyer, Mn, Johannesson, M, Visscher, Pm, Koellinger, Pd, Cesarini, D, and Benjamin, Dj

Subjects
Netherlands Twin Register (NTR), 0301 basic medicine, Male, Parents, education: longevity: prediction: polygenic score [genetics], Multifactorial Inheritance, polygenic, Lebenserwartung, Cohort Studies, 0302 clinical medicine, Databases, Genetic, Medicine, genetics, polygenic score, longevity, education, gene, Soziales und Gesundheit, media_common, Aged, 80 and over, education, Multidisciplinary, Longevity, Middle Aged, Biobank, humanities, 3. Good health, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Cohort, Educational Status, Female, Cohort study, Estonia, education, longevity, polygenic, Offspring, media_common.quotation_subject, Kultursektor, Prognose, Lernen, Lower risk, Education, 03 medical and health sciences, longevity, SDG 3 - Good Health and Well-being, Commentaries, Polygenic score, Journal Article, Genetics, Humans, Non-Profit-Sektor, Genetic Association Studies, Aged, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, ta1184, Genetic Variation, prediction, Educational attainment, United Kingdom, Gesundheitsstatistik, 030104 developmental biology, Genetic epidemiology, Scotland, Gesundheitszustand, Genetische Forschung, business, Prediction, Bildung, 030217 neurology & neurosurgery, Demography
Abstract

Educational attainment is associated with many health outcomes, including longevity. It is also known to be substantially heritable. Here, we used data from three large genetic epidemiology cohort studies (Generation Scotland, n = ∼17,000; UK Biobank, n = ∼115,000; and the Estonian Biobank, n = ∼6,000) to test whether education-linked genetic variants can predict lifespan length. We did so by using cohort members' polygenic profile score for education to predict their parents' longevity. Across the three cohorts, meta-analysis showed that a 1 SD higher polygenic education score was associated with ∼2.7% lower mortality risk for both mothers (total n deaths = 79,702) and ∼2.4% lower risk for fathers (total n deaths = 97,630). On average, the parents of offspring in the upper third of the polygenic score distribution lived 0.55 y longer compared with those of offspring in the lower third. Overall, these results indicate that the genetic contributions to educational attainment are useful in the prediction of human longevity. Marioni RE, Ritchie SJ, Joshi PK, Hagenaars SP, Okbay A, Fischer K, Adams MJ, Hill WD, Davies G, Social Science Genetic Association Consortium, Nagy R, Amador C, Läll K, Metspalu A, Liewald DC, Campbell A, Wilson JF, Hayward C, Esko T, Porteous DJ, Proceedings of the National Academy of Sciences of the United States of America, 2016, vol. 113, no. 47, pp. 13366-13371, 2016 Refereed/Peer-reviewed

Published
2016

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

Author

van de Vegte YJ, Eppinga RN, van der Ende MY, Hagemeijer YP, Mahendran Y, Salfati E, Smith AV, Tan VY, Arking DE, Ntalla I, Appel EV, Schurmann C, Brody JA, Rueedi R, Polasek O, Sveinbjornsson G, Lecoeur C, Ladenvall C, Zhao JH, Isaacs A, Wang L, Luan J, Hwang SJ, Mononen N, Auro K, Jackson AU, Bielak LF, Zeng L, Shah N, Nethander M, Campbell A, Rankinen T, Pechlivanis S, Qi L, Zhao W, Rizzi F, Tanaka T, Robino A, Cocca M, Lange L, Müller-Nurasyid M, Roselli C, Zhang W, Kleber ME, Guo X, Lin HJ, Pavani F, Galesloot TE, Noordam R, Milaneschi Y, Schraut KE, den Hoed M, Degenhardt F, Trompet S, van den Berg ME, Pistis G, Tham YC, Weiss S, Sim XS, Li HL, van der Most PJ, Nolte IM, Lyytikäinen LP, Said MA, Witte DR, Iribarren C, Launer L, Ring SM, de Vries PS, Sever P, Linneberg A, Bottinger EP, Padmanabhan S, Psaty BM, Sotoodehnia N, Kolcic I, Arnar DO, Gudbjartsson DF, Holm H, Balkau B, Silva CT, Newton-Cheh CH, Nikus K, Salo P, Mohlke KL, Peyser PA, Schunkert H, Lorentzon M, Lahti J, Rao DC, Cornelis MC, Faul JD, Smith JA, Stolarz-Skrzypek K, Bandinelli S, Concas MP, Sinagra G, Meitinger T, Waldenberger M, Sinner MF, Strauch K, Delgado GE, Taylor KD, Yao J, Foco L, Melander O, de Graaf J, de Mutsert R, de Geus EJC, Johansson Å, Joshi PK, Lind L, Franke A, Macfarlane PW, Tarasov KV, Tan N, Felix SB, Tai ES, Quek DQ, Snieder H, Ormel J, Ingelsson M, Lindgren C, Morris AP, Raitakari OT, Hansen T, Assimes T, Gudnason V, Timpson NJ, Morrison AC, Munroe PB, Strachan DP, Grarup N, Loos RJF, Heckbert SR, Vollenweider P, Hayward C, Stefansson K, Froguel P, Groop L, Wareham NJ, van Duijn CM, Feitosa MF, O'Donnell CJ, Kähönen M, Perola M, Boehnke M, Kardia SLR, Erdmann J, Palmer CNA, Ohlsson C, Porteous DJ, Eriksson JG, Bouchard C, Moebus S, Kraft P, Weir DR, Cusi D, Ferrucci L, Ulivi S, Girotto G, Correa A, Kääb S, Peters A, Chambers JC, Kooner JS, März W, Rotter JI, Hicks AA, Smith JG, Kiemeney LALM, Mook-Kanamori DO, Penninx BWJH, Gyllensten U, Wilson JF, Burgess S, Sundström J, Lieb W, Jukema JW, Eijgelsheim M, Lakatta ELM, Cheng CY, Dörr M, Wong TY, Sabanayagam C, Oldehinkel AJ, Riese H, Lehtimäki T, Verweij N, and van der Harst P

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

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development., (© 2023. The Author(s).)

Published
2023
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7. Bone mineral density loci specific to the skull portray potential pleiotropic effects on craniosynostosis.

Author

Medina-Gomez C, Mullin BH, Chesi A, Prijatelj V, Kemp JP, Shochat-Carvalho C, Trajanoska K, Wang C, Joro R, Evans TE, Schraut KE, Li-Gao R, Ahluwalia TS, Zillikens MC, Zhu K, Mook-Kanamori DO, Evans DS, Nethander M, Knol MJ, Thorleifsson G, Prokic I, Zemel B, Broer L, McGuigan FE, van Schoor NM, Reppe S, Pawlak MA, Ralston SH, van der Velde N, Lorentzon M, Stefansson K, Adams HHH, Wilson SG, Ikram MA, Walsh JP, Lakka TA, Gautvik KM, Wilson JF, Orwoll ES, van Duijn CM, Bønnelykke K, Uitterlinden AG, Styrkársdóttir U, Akesson KE, Spector TD, Tobias JH, Ohlsson C, Felix JF, Bisgaard H, Grant SFA, Richards JB, Evans DM, van der Eerden B, van de Peppel J, Ackert-Bicknell C, Karasik D, Kague E, and Rivadeneira F

Subjects
Animals, Genome-Wide Association Study, Zebrafish genetics, Skull, Transcription Factors genetics, Bone Density genetics, Craniosynostoses genetics
Abstract

Skull bone mineral density (SK-BMD) provides a suitable trait for the discovery of key genes in bone biology, particularly to intramembranous ossification, not captured at other skeletal sites. We perform a genome-wide association meta-analysis (n ~ 43,800) of SK-BMD, identifying 59 loci, collectively explaining 12.5% of the trait variance. Association signals cluster within gene-sets involved in skeletal development and osteoporosis. Among the four novel loci (ZIC1, PRKAR1A, AZIN1/ATP6V1C1, GLRX3), there are factors implicated in intramembranous ossification and as we show, inherent to craniosynostosis processes. Functional follow-up in zebrafish confirms the importance of ZIC1 on cranial suture patterning. Likewise, we observe abnormal cranial bone initiation that culminates in ectopic sutures and reduced BMD in mosaic atp6v1c1 knockouts. Mosaic prkar1a knockouts present asymmetric bone growth and, conversely, elevated BMD. In light of this evidence linking SK-BMD loci to craniofacial abnormalities, our study provides new insight into the pathophysiology, diagnosis and treatment of skeletal diseases., (© 2023. The Author(s).)

Published
2023
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8. A multi-omics study of circulating phospholipid markers of blood pressure.

Author

Liu J, de Vries PS, Del Greco M F, Johansson Å, Schraut KE, Hayward C, van Dijk KW, Franco OH, Hicks AA, Vitart V, Rudan I, Campbell H, Polašek O, Pramstaller PP, Wilson JF, Gyllensten U, van Duijn CM, Dehghan A, and Demirkan A

Subjects
Adult, Aged, Biomarkers blood, Cardiometabolic Risk Factors, Cohort Studies, Diastole, Female, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Systole, Blood Pressure, Computational Biology, Hypertension blood, Phospholipids blood
Abstract

High-throughput techniques allow us to measure a wide-range of phospholipids which can provide insight into the mechanisms of hypertension. We aimed to conduct an in-depth multi-omics study of various phospholipids with systolic blood pressure (SBP) and diastolic blood pressure (DBP). The associations of blood pressure and 151 plasma phospholipids measured by electrospray ionization tandem mass spectrometry were performed by linear regression in five European cohorts (n = 2786 in discovery and n = 1185 in replication). We further explored the blood pressure-related phospholipids in Erasmus Rucphen Family (ERF) study by associating them with multiple cardiometabolic traits (linear regression) and predicting incident hypertension (Cox regression). Mendelian Randomization (MR) and phenome-wide association study (Phewas) were also explored to further investigate these association results. We identified six phosphatidylethanolamines (PE 38:3, PE 38:4, PE 38:6, PE 40:4, PE 40:5 and PE 40:6) and two phosphatidylcholines (PC 32:1 and PC 40:5) which together predicted incident hypertension with an area under the ROC curve (AUC) of 0.61. The identified eight phospholipids are strongly associated with triglycerides, obesity related traits (e.g. waist, waist-hip ratio, total fat percentage, body mass index, lipid-lowering medication, and leptin), diabetes related traits (e.g. glucose, insulin resistance and insulin) and prevalent type 2 diabetes. The genetic determinants of these phospholipids also associated with many lipoproteins, heart rate, pulse rate and blood cell counts. No significant association was identified by bi-directional MR approach. We identified eight blood pressure-related circulating phospholipids that have a predictive value for incident hypertension. Our cross-omics analyses show that phospholipid metabolites in the circulation may yield insight into blood pressure regulation and raise a number of testable hypothesis for future research., (© 2022. The Author(s).)

Published
2022
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9. Genetic insights into biological mechanisms governing human ovarian ageing.

Author

Ruth KS, Day FR, Hussain J, Martínez-Marchal A, Aiken CE, Azad A, Thompson DJ, Knoblochova L, Abe H, Tarry-Adkins JL, Gonzalez JM, Fontanillas P, Claringbould A, Bakker OB, Sulem P, Walters RG, Terao C, Turon S, Horikoshi M, Lin K, Onland-Moret NC, Sankar A, Hertz EPT, Timshel PN, Shukla V, Borup R, Olsen KW, Aguilera P, Ferrer-Roda M, Huang Y, Stankovic S, Timmers PRHJ, Ahearn TU, Alizadeh BZ, Naderi E, Andrulis IL, Arnold AM, Aronson KJ, Augustinsson A, Bandinelli S, Barbieri CM, Beaumont RN, Becher H, Beckmann MW, Benonisdottir S, Bergmann S, Bochud M, Boerwinkle E, Bojesen SE, Bolla MK, Boomsma DI, Bowker N, Brody JA, Broer L, Buring JE, Campbell A, Campbell H, Castelao JE, Catamo E, Chanock SJ, Chenevix-Trench G, Ciullo M, Corre T, Couch FJ, Cox A, Crisponi L, Cross SS, Cucca F, Czene K, Smith GD, de Geus EJCN, de Mutsert R, De Vivo I, Demerath EW, Dennis J, Dunning AM, Dwek M, Eriksson M, Esko T, Fasching PA, Faul JD, Ferrucci L, Franceschini N, Frayling TM, Gago-Dominguez M, Mezzavilla M, García-Closas M, Gieger C, Giles GG, Grallert H, Gudbjartsson DF, Gudnason V, Guénel P, Haiman CA, Håkansson N, Hall P, Hayward C, He C, He W, Heiss G, Høffding MK, Hopper JL, Hottenga JJ, Hu F, Hunter D, Ikram MA, Jackson RD, Joaquim MDR, John EM, Joshi PK, Karasik D, Kardia SLR, Kartsonaki C, Karlsson R, Kitahara CM, Kolcic I, Kooperberg C, Kraft P, Kurian AW, Kutalik Z, La Bianca M, LaChance G, Langenberg C, Launer LJ, Laven JSE, Lawlor DA, Le Marchand L, Li J, Lindblom A, Lindstrom S, Lindstrom T, Linet M, Liu Y, Liu S, Luan J, Mägi R, Magnusson PKE, Mangino M, Mannermaa A, Marco B, Marten J, Martin NG, Mbarek H, McKnight B, Medland SE, Meisinger C, Meitinger T, Menni C, Metspalu A, Milani L, Milne RL, Montgomery GW, Mook-Kanamori DO, Mulas A, Mulligan AM, Murray A, Nalls MA, Newman A, Noordam R, Nutile T, Nyholt DR, Olshan AF, Olsson H, Painter JN, Patel AV, Pedersen NL, Perjakova N, Peters A, Peters U, Pharoah PDP, Polasek O, Porcu E, Psaty BM, Rahman I, Rennert G, Rennert HS, Ridker PM, Ring SM, Robino A, Rose LM, Rosendaal FR, Rossouw J, Rudan I, Rueedi R, Ruggiero D, Sala CF, Saloustros E, Sandler DP, Sanna S, Sawyer EJ, Sarnowski C, Schlessinger D, Schmidt MK, Schoemaker MJ, Schraut KE, Scott C, Shekari S, Shrikhande A, Smith AV, Smith BH, Smith JA, Sorice R, Southey MC, Spector TD, Spinelli JJ, Stampfer M, Stöckl D, van Meurs JBJ, Strauch K, Styrkarsdottir U, Swerdlow AJ, Tanaka T, Teras LR, Teumer A, Þorsteinsdottir U, Timpson NJ, Toniolo D, Traglia M, Troester MA, Truong T, Tyrrell J, Uitterlinden AG, Ulivi S, Vachon CM, Vitart V, Völker U, Vollenweider P, Völzke H, Wang Q, Wareham NJ, Weinberg CR, Weir DR, Wilcox AN, van Dijk KW, Willemsen G, Wilson JF, Wolffenbuttel BHR, Wolk A, Wood AR, Zhao W, Zygmunt M, Chen Z, Li L, Franke L, Burgess S, Deelen P, Pers TH, Grøndahl ML, Andersen CY, Pujol A, Lopez-Contreras AJ, Daniel JA, Stefansson K, Chang-Claude J, van der Schouw YT, Lunetta KL, Chasman DI, Easton DF, Visser JA, Ozanne SE, Namekawa SH, Solc P, Murabito JM, Ong KK, Hoffmann ER, Murray A, Roig I, and Perry JRB

Subjects
Adult, Alleles, Animals, Bone and Bones metabolism, Checkpoint Kinase 1 genetics, Checkpoint Kinase 2 genetics, Diabetes Mellitus, Type 2, Diet, Europe ethnology, Asia, Eastern ethnology, Female, Fertility genetics, Fragile X Mental Retardation Protein genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Healthy Aging genetics, Humans, Longevity genetics, Menopause genetics, Menopause, Premature genetics, Mice, Mice, Inbred C57BL, Middle Aged, Primary Ovarian Insufficiency genetics, Uterus, Aging genetics, Ovary metabolism
Abstract

Reproductive longevity is essential for fertility and influences healthy ageing in women 1,2 , but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations 3 . The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Published
2021
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10. Novel Genetic Locus Influencing Retinal Venular Tortuosity Is Also Associated With Risk of Coronary Artery Disease.

Author

Veluchamy A, Ballerini L, Vitart V, Schraut KE, Kirin M, Campbell H, Joshi PK, Relan D, Harris S, Brown E, Vaidya SS, Dhillon B, Zhou K, Pearson ER, Hayward C, Polasek O, Deary IJ, MacGillivray T, Wilson JF, Trucco E, Palmer CNA, and Doney ASF

Subjects
Coronary Artery Disease diagnosis, Coronary Artery Disease etiology, Humans, Phenotype, Retinal Diseases complications, Retinal Diseases diagnosis, Retinal Vessels diagnostic imaging, Risk Factors, Coronary Artery Disease genetics, Genetic Predisposition to Disease, Genome-Wide Association Study methods, Retinal Diseases genetics, Retinal Vessels abnormalities, Venules abnormalities
Abstract

Objective: The retina may provide readily accessible imaging biomarkers of global cardiovascular health. Increasing evidence suggests variation in retinal vascular traits is highly heritable. This study aimed to identify the genetic determinants of retinal vascular traits. Approach and Results: We conducted a meta-analysis of genome-wide association studies for quantitative retinal vascular traits derived using semi-automatic image analysis of digital retinal photographs from the GoDARTS (Genetics of Diabetes Audit and Research in Tayside; N=1736) and ORCADES (Orkney Complex Disease Study; N=1358) cohorts. We identified a novel genome-wide significant locus at 19q13 ( ACTN4/CAPN12 ) for retinal venular tortuosity ( TortV ), and one at 13q34 ( COL4A2 ) for retinal arteriolar tortuosity ( TortA ); these 2 loci were subsequently confirmed in 3 independent cohorts (N total =1413). In the combined analysis of discovery and replication cohorts, the lead single-nucleotide polymorphism in ACTN4 / CAPN12 was rs1808382 (β s.d. =-0.109; SE=0.015; P =2.39×10- 13 ) and in COL4A2 was rs7991229 (β s.d. =0.103; SE=0.015; P =4.66×10- 12 ). Notably, the ACTN4 / CAPN12 locus associated with TortV is also associated with coronary artery disease, heart rate, and atrial fibrillation., Conclusions: Genetic determinants of retinal vascular tortuosity are also linked to cardiovascular health. These findings provide a molecular pathophysiological foundation for the use of retinal vascular traits as biomarkers for cardiovascular diseases.

Published
2019
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11. Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders.

Author

Ligthart S, Vaez A, Võsa U, Stathopoulou MG, de Vries PS, Prins BP, Van der Most PJ, Tanaka T, Naderi E, Rose LM, Wu Y, Karlsson R, Barbalic M, Lin H, Pool R, Zhu G, Macé A, Sidore C, Trompet S, Mangino M, Sabater-Lleal M, Kemp JP, Abbasi A, Kacprowski T, Verweij N, Smith AV, Huang T, Marzi C, Feitosa MF, Lohman KK, Kleber ME, Milaneschi Y, Mueller C, Huq M, Vlachopoulou E, Lyytikäinen LP, Oldmeadow C, Deelen J, Perola M, Zhao JH, Feenstra B, Amini M, Lahti J, Schraut KE, Fornage M, Suktitipat B, Chen WM, Li X, Nutile T, Malerba G, Luan J, Bak T, Schork N, Del Greco M F, Thiering E, Mahajan A, Marioni RE, Mihailov E, Eriksson J, Ozel AB, Zhang W, Nethander M, Cheng YC, Aslibekyan S, Ang W, Gandin I, Yengo L, Portas L, Kooperberg C, Hofer E, Rajan KB, Schurmann C, den Hollander W, Ahluwalia TS, Zhao J, Draisma HHM, Ford I, Timpson N, Teumer A, Huang H, Wahl S, Liu Y, Huang J, Uh HW, Geller F, Joshi PK, Yanek LR, Trabetti E, Lehne B, Vozzi D, Verbanck M, Biino G, Saba Y, Meulenbelt I, O'Connell JR, Laakso M, Giulianini F, Magnusson PKE, Ballantyne CM, Hottenga JJ, Montgomery GW, Rivadineira F, Rueedi R, Steri M, Herzig KH, Stott DJ, Menni C, Frånberg M, St Pourcain B, Felix SB, Pers TH, Bakker SJL, Kraft P, Peters A, Vaidya D, Delgado G, Smit JH, Großmann V, Sinisalo J, Seppälä I, Williams SR, Holliday EG, Moed M, Langenberg C, Räikkönen K, Ding J, Campbell H, Sale MM, Chen YI, James AL, Ruggiero D, Soranzo N, Hartman CA, Smith EN, Berenson GS, Fuchsberger C, Hernandez D, Tiesler CMT, Giedraitis V, Liewald D, Fischer K, Mellström D, Larsson A, Wang Y, Scott WR, Lorentzon M, Beilby J, Ryan KA, Pennell CE, Vuckovic D, Balkau B, Concas MP, Schmidt R, Mendes de Leon CF, Bottinger EP, Kloppenburg M, Paternoster L, Boehnke M, Musk AW, Willemsen G, Evans DM, Madden PAF, Kähönen M, Kutalik Z, Zoledziewska M, Karhunen V, Kritchevsky SB, Sattar N, Lachance G, Clarke R, Harris TB, Raitakari OT, Attia JR, van Heemst D, Kajantie E, Sorice R, Gambaro G, Scott RA, Hicks AA, Ferrucci L, Standl M, Lindgren CM, Starr JM, Karlsson M, Lind L, Li JZ, Chambers JC, Mori TA, de Geus EJCN, Heath AC, Martin NG, Auvinen J, Buckley BM, de Craen AJM, Waldenberger M, Strauch K, Meitinger T, Scott RJ, McEvoy M, Beekman M, Bombieri C, Ridker PM, Mohlke KL, Pedersen NL, Morrison AC, Boomsma DI, Whitfield JB, Strachan DP, Hofman A, Vollenweider P, Cucca F, Jarvelin MR, Jukema JW, Spector TD, Hamsten A, Zeller T, Uitterlinden AG, Nauck M, Gudnason V, Qi L, Grallert H, Borecki IB, Rotter JI, März W, Wild PS, Lokki ML, Boyle M, Salomaa V, Melbye M, Eriksson JG, Wilson JF, Penninx BWJH, Becker DM, Worrall BB, Gibson G, Krauss RM, Ciullo M, Zaza G, Wareham NJ, Oldehinkel AJ, Palmer LJ, Murray SS, Pramstaller PP, Bandinelli S, Heinrich J, Ingelsson E, Deary IJ, Mägi R, Vandenput L, van der Harst P, Desch KC, Kooner JS, Ohlsson C, Hayward C, Lehtimäki T, Shuldiner AR, Arnett DK, Beilin LJ, Robino A, Froguel P, Pirastu M, Jess T, Koenig W, Loos RJF, Evans DA, Schmidt H, Smith GD, Slagboom PE, Eiriksdottir G, Morris AP, Psaty BM, Tracy RP, Nolte IM, Boerwinkle E, Visvikis-Siest S, Reiner AP, Gross M, Bis JC, Franke L, Franco OH, Benjamin EJ, Chasman DI, Dupuis J, Snieder H, Dehghan A, and Alizadeh BZ

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Biomarkers metabolism, Bipolar Disorder genetics, Bipolar Disorder metabolism, Body Mass Index, C-Reactive Protein genetics, Child, Female, Genome-Wide Association Study methods, Humans, Inflammation metabolism, Liver metabolism, Liver pathology, Male, Mendelian Randomization Analysis methods, Middle Aged, Schizophrenia genetics, Schizophrenia metabolism, Young Adult, Genetic Loci genetics, Inflammation genetics, Metabolic Networks and Pathways genetics
Abstract

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10 -8 ). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences., (Copyright © 2018 American Society of Human Genetics. All rights reserved.)

Published
2018
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12. Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects.

Author

Medina-Gomez C, Kemp JP, Trajanoska K, Luan J, Chesi A, Ahluwalia TS, Mook-Kanamori DO, Ham A, Hartwig FP, Evans DS, Joro R, Nedeljkovic I, Zheng HF, Zhu K, Atalay M, Liu CT, Nethander M, Broer L, Porleifsson G, Mullin BH, Handelman SK, Nalls MA, Jessen LE, Heppe DHM, Richards JB, Wang C, Chawes B, Schraut KE, Amin N, Wareham N, Karasik D, Van der Velde N, Ikram MA, Zemel BS, Zhou Y, Carlsson CJ, Liu Y, McGuigan FE, Boer CG, Bønnelykke K, Ralston SH, Robbins JA, Walsh JP, Zillikens MC, Langenberg C, Li-Gao R, Williams FMK, Harris TB, Akesson K, Jackson RD, Sigurdsson G, den Heijer M, van der Eerden BCJ, van de Peppel J, Spector TD, Pennell C, Horta BL, Felix JF, Zhao JH, Wilson SG, de Mutsert R, Bisgaard H, Styrkársdóttir U, Jaddoe VW, Orwoll E, Lakka TA, Scott R, Grant SFA, Lorentzon M, van Duijn CM, Wilson JF, Stefansson K, Psaty BM, Kiel DP, Ohlsson C, Ntzani E, van Wijnen AJ, Forgetta V, Ghanbari M, Logan JG, Williams GR, Bassett JHD, Croucher PI, Evangelou E, Uitterlinden AG, Ackert-Bicknell CL, Tobias JH, Evans DM, and Rivadeneira F

Subjects
Adolescent, Age Factors, Animals, Child, Child, Preschool, Genetic Loci, Humans, Infant, Infant, Newborn, Mice, Knockout, Polymorphism, Single Nucleotide genetics, Quantitative Trait, Heritable, Regression Analysis, Bone Density genetics, Genome-Wide Association Study
Abstract

Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course., (Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2018
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13. Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity.

Author

Joshi PK, Pirastu N, Kentistou KA, Fischer K, Hofer E, Schraut KE, Clark DW, Nutile T, Barnes CLK, Timmers PRHJ, Shen X, Gandin I, McDaid AF, Hansen TF, Gordon SD, Giulianini F, Boutin TS, Abdellaoui A, Zhao W, Medina-Gomez C, Bartz TM, Trompet S, Lange LA, Raffield L, van der Spek A, Galesloot TE, Proitsi P, Yanek LR, Bielak LF, Payton A, Murgia F, Concas MP, Biino G, Tajuddin SM, Seppälä I, Amin N, Boerwinkle E, Børglum AD, Campbell A, Demerath EW, Demuth I, Faul JD, Ford I, Gialluisi A, Gögele M, Graff M, Hingorani A, Hottenga JJ, Hougaard DM, Hurme MA, Ikram MA, Jylhä M, Kuh D, Ligthart L, Lill CM, Lindenberger U, Lumley T, Mägi R, Marques-Vidal P, Medland SE, Milani L, Nagy R, Ollier WER, Peyser PA, Pramstaller PP, Ridker PM, Rivadeneira F, Ruggiero D, Saba Y, Schmidt R, Schmidt H, Slagboom PE, Smith BH, Smith JA, Sotoodehnia N, Steinhagen-Thiessen E, van Rooij FJA, Verbeek AL, Vermeulen SH, Vollenweider P, Wang Y, Werge T, Whitfield JB, Zonderman AB, Lehtimäki T, Evans MK, Pirastu M, Fuchsberger C, Bertram L, Pendleton N, Kardia SLR, Ciullo M, Becker DM, Wong A, Psaty BM, van Duijn CM, Wilson JG, Jukema JW, Kiemeney L, Uitterlinden AG, Franceschini N, North KE, Weir DR, Metspalu A, Boomsma DI, Hayward C, Chasman D, Martin NG, Sattar N, Campbell H, Esko T, Kutalik Z, and Wilson JF

Subjects
Alleles, Body Mass Index, Coronary Disease blood, Coronary Disease etiology, Education, Genetic Predisposition to Disease genetics, Genome-Wide Association Study, Humans, Insulin Resistance genetics, Lipoproteins, HDL blood, Lung Neoplasms blood, Lung Neoplasms genetics, Obesity complications, Obesity genetics, Polymorphism, Single Nucleotide, Smoking adverse effects, Socioeconomic Factors, HLA-DQ alpha-Chains genetics, HLA-DRB1 Chains genetics, Life Style, Lipoprotein(a) genetics, Longevity genetics
Abstract

Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents' survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan.Variability in human longevity is genetically influenced. Using genetic data of parental lifespan, the authors identify associations at HLA-DQA/DRB1 and LPA and find that genetic variants that increase educational attainment have a positive effect on lifespan whereas increasing BMI negatively affects lifespan.

Published
2017
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14. 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 LP, Cousminer DL, Wu Y, Thiering E, Wang CA, Have CT, Hottenga JJ, 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, Ganesh SK, van Rooij FJ, Jones SE, Loh PR, 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 CE, Willemsen G, Appel EVR, Fonvig CE, Trier C, Tiesler CM, Standl M, Kutalik Z, Bonas-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, Lowe WL Jr, Tönjes A, Stumvoll M, Lindi V, Lakka TA, van Duijn CM, Kiess W, Körner A, Sørensen TI, Niinikoski H, Pahkala K, Raitakari OT, Zeggini E, Dedoussis GV, Teo YY, Saw SM, Melbye M, Campbell H, Wilson JF, Vrijheid M, de Geus EJ, Boomsma DI, Kadarmideen HN, Holm JC, Hansen T, Sebert S, Hattersley AT, Beilin LJ, Newnham JP, Pennell CE, Heinrich J, Adair LS, Borja JB, Mohlke KL, Eriksson JG, Widén EE, 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 VW, Jarvelin MR, Grant SF, Vaag AA, Lawlor DA, Frayling TM, Davey Smith G, Morris AP, Ong KK, Felix JF, Timpson NJ, Perry JR, Evans DM, McCarthy MI, and Freathy RM

Subjects
Adult, Anthropometry, Blood Pressure genetics, Chromatin Assembly and Disassembly, Cohort Studies, Datasets as Topic, Female, Genetic Loci genetics, Genetic Variation genetics, Genomic Imprinting genetics, Genotype, Glucose metabolism, Glycogen biosynthesis, Humans, Insulin metabolism, Male, Phenotype, Signal Transduction, Aging genetics, Birth Weight genetics, Coronary Artery Disease genetics, Diabetes Mellitus, Type 2 genetics, Fetus metabolism, Genetic Predisposition to Disease, Genome-Wide Association Study
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 (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 (R g  = -0.22, P = 5.5 × 10 -13 ), T2D (R g  = -0.27, P = 1.1 × 10 -6 ) and coronary artery disease (R g  = -0.30, 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 (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., Competing Interests: One of the authors discloses competing financial interests: Krina Zondervan has a scientific collaboration with Bayer HealthCare Ltd. and Population Diagnostics Inc.

Published
2016
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15. Genome-wide association study identifies 74 loci associated with educational attainment.

Author

Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, Turley P, Chen GB, Emilsson V, Meddens SF, Oskarsson S, Pickrell JK, Thom K, Timshel P, de Vlaming R, Abdellaoui A, Ahluwalia TS, Bacelis J, Baumbach C, Bjornsdottir G, Brandsma JH, Pina Concas M, Derringer J, Furlotte NA, Galesloot TE, Girotto G, Gupta R, Hall LM, Harris SE, Hofer E, Horikoshi M, Huffman JE, Kaasik K, Kalafati IP, Karlsson R, Kong A, Lahti J, van der Lee SJ, deLeeuw C, Lind PA, Lindgren KO, Liu T, Mangino M, Marten J, Mihailov E, Miller MB, van der Most PJ, Oldmeadow C, Payton A, Pervjakova N, Peyrot WJ, Qian Y, Raitakari O, Rueedi R, Salvi E, Schmidt B, Schraut KE, Shi J, Smith AV, Poot RA, St Pourcain B, Teumer A, Thorleifsson G, Verweij N, Vuckovic D, Wellmann J, Westra HJ, Yang J, Zhao W, Zhu Z, Alizadeh BZ, Amin N, Bakshi A, Baumeister SE, Biino G, Bønnelykke K, Boyle PA, Campbell H, Cappuccio FP, Davies G, De Neve JE, Deloukas P, Demuth I, Ding J, Eibich P, Eisele L, Eklund N, Evans DM, Faul JD, Feitosa MF, Forstner AJ, Gandin I, Gunnarsson B, Halldórsson BV, Harris TB, Heath AC, Hocking LJ, Holliday EG, Homuth G, Horan MA, Hottenga JJ, de Jager PL, Joshi PK, Jugessur A, Kaakinen MA, Kähönen M, Kanoni S, Keltigangas-Järvinen L, Kiemeney LA, Kolcic I, Koskinen S, Kraja AT, Kroh M, Kutalik Z, Latvala A, Launer LJ, Lebreton MP, Levinson DF, Lichtenstein P, Lichtner P, Liewald DC, Loukola A, Madden PA, Mägi R, Mäki-Opas T, Marioni RE, Marques-Vidal P, Meddens GA, McMahon G, Meisinger C, Meitinger T, Milaneschi Y, Milani L, Montgomery GW, Myhre R, Nelson CP, Nyholt DR, Ollier WE, Palotie A, Paternoster L, Pedersen NL, Petrovic KE, Porteous DJ, Räikkönen K, Ring SM, Robino A, Rostapshova O, Rudan I, Rustichini A, Salomaa V, Sanders AR, Sarin AP, Schmidt H, Scott RJ, Smith BH, Smith JA, Staessen JA, Steinhagen-Thiessen E, Strauch K, Terracciano A, Tobin MD, Ulivi S, Vaccargiu S, Quaye L, van Rooij FJ, Venturini C, Vinkhuyzen AA, Völker U, Völzke H, Vonk JM, Vozzi D, Waage J, Ware EB, Willemsen G, Attia JR, Bennett DA, Berger K, Bertram L, Bisgaard H, Boomsma DI, Borecki IB, Bültmann U, Chabris CF, Cucca F, Cusi D, Deary IJ, Dedoussis GV, van Duijn CM, Eriksson JG, Franke B, Franke L, Gasparini P, Gejman PV, Gieger C, Grabe HJ, Gratten J, Groenen PJ, Gudnason V, van der Harst P, Hayward C, Hinds DA, Hoffmann W, Hyppönen E, Iacono WG, Jacobsson B, Järvelin MR, Jöckel KH, Kaprio J, Kardia SL, Lehtimäki T, Lehrer SF, Magnusson PK, Martin NG, McGue M, Metspalu A, Pendleton N, Penninx BW, Perola M, Pirastu N, Pirastu M, Polasek O, Posthuma D, Power C, Province MA, Samani NJ, Schlessinger D, Schmidt R, Sørensen TI, Spector TD, Stefansson K, Thorsteinsdottir U, Thurik AR, Timpson NJ, Tiemeier H, Tung JY, Uitterlinden AG, Vitart V, Vollenweider P, Weir DR, Wilson JF, Wright AF, Conley DC, Krueger RF, Davey Smith G, Hofman A, Laibson DI, Medland SE, Meyer MN, Yang J, Johannesson M, Visscher PM, Esko T, Koellinger PD, Cesarini D, and Benjamin DJ

Subjects
Alzheimer Disease genetics, Bipolar Disorder genetics, Cognition, Computational Biology, Gene-Environment Interaction, Humans, Molecular Sequence Annotation, Schizophrenia genetics, United Kingdom, Brain metabolism, Educational Status, Fetus metabolism, Gene Expression Regulation genetics, Genome-Wide Association Study, Polymorphism, Single Nucleotide genetics
Abstract

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Published
2016
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16. Variants near CHRNA3/5 and APOE have age- and sex-related effects on human lifespan.

Author

Joshi PK, Fischer K, Schraut KE, Campbell H, Esko T, and Wilson JF

Subjects
Adult, Age Factors, Aged, Aged, 80 and over, Apolipoproteins E physiology, Cohort Studies, Female, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Nerve Tissue Proteins physiology, Proportional Hazards Models, Receptors, Nicotinic physiology, Sex Factors, United Kingdom, Apolipoproteins E genetics, Longevity genetics, Nerve Tissue Proteins genetics, Receptors, Nicotinic genetics
Abstract

Lifespan is a trait of enormous personal interest. Research into the biological basis of human lifespan, however, is hampered by the long time to death. Using a novel approach of regressing (272,081) parental lifespans beyond age 40 years on participant genotype in a new large data set (UK Biobank), we here show that common variants near the apolipoprotein E and nicotinic acetylcholine receptor subunit alpha 5 genes are associated with lifespan. The effects are strongly sex and age dependent, with APOE ɛ4 differentially influencing maternal lifespan (P=4.2 × 10(-15), effect -1.24 years of maternal life per imputed risk allele in parent; sex difference, P=0.011), and a locus near CHRNA3/5 differentially affecting paternal lifespan (P=4.8 × 10(-11), effect -0.86 years per allele; sex difference P=0.075). Rare homozygous carriers of the risk alleles at both loci are predicted to have 3.3-3.7 years shorter lives.

Published
2016
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17. Fine mapping the CETP region reveals a common intronic insertion associated to HDL-C.

Author

van Leeuwen EM, Huffman JE, Bis JC, Isaacs A, Mulder M, Sabo A, Smith AV, Demissie S, Manichaikul A, Brody JA, Feitosa MF, Duan Q, Schraut KE, Navarro P, van Vliet-Ostaptchouk JV, Zhu G, Mbarek H, Trompet S, Verweij N, Lyytikäinen LP, Deelen J, Nolte IM, van der Laan SW, Davies G, Vermeij-Verdoold AJ, van Oosterhout AA, Vergeer-Drop JM, Arking DE, Trochet H, Medina-Gomez C, Rivadeneira F, Uitterlinden AG, Dehghan A, Franco OH, Sijbrands EJ, Hofman A, White CC, Mychaleckyj JC, Peloso GM, Swertz MA, Willemsen G, de Geus EJ, Milaneschi Y, Penninx BW, Ford I, Buckley BM, de Craen AJ, Starr JM, Deary IJ, Pasterkamp G, Oldehinkel AJ, Snieder H, Slagboom PE, Nikus K, Kähönen M, Lehtimäki T, Viikari JS, Raitakari OT, van der Harst P, Jukema JW, Hottenga JJ, Boomsma DI, Whitfield JB, Montgomery G, Martin NG, Polasek O, Vitart V, Hayward C, Kolcic I, Wright AF, Rudan I, Joshi PK, Wilson JF, Lange LA, Wilson JG, Gudnason V, Harris TB, Morrison AC, Borecki IB, Rich SS, Padmanabhan S, Psaty BM, Rotter JI, Smith BH, Boerwinkle E, Cupples LA, and van Duijn C

Abstract

Background: Individuals with exceptional longevity and their offspring have significantly larger high-density lipoprotein concentrations (HDL-C) particle sizes due to the increased homozygosity for the I405V variant in the cholesteryl ester transfer protein ( CETP) gene. In this study, we investigate the association of CETP and HDL-C further to identify novel, independent CETP variants associated with HDL-C in humans., Methods: We performed a meta-analysis of HDL-C within the CETP region using 59,432 individuals imputed with 1000 Genomes data. We performed replication in an independent sample of 47,866 individuals and validation was done by Sanger sequencing., Results: The meta-analysis of HDL-C within the CETP region identified five independent variants, including an exonic variant and a common intronic insertion. We replicated these 5 variants significantly in an independent sample of 47,866 individuals. Sanger sequencing of the insertion within a single family confirmed segregation of this variant. The strongest reported association between HDL-C and CETP variants, was rs3764261; however, after conditioning on the five novel variants we identified the support for rs3764261 was highly reduced ( β unadjusted =3.179 mg/dl ( P value=5.25×10 -509 ), β adjusted =0.859 mg/dl ( P value=9.51×10 -25 )), and this finding suggests that these five novel variants may partly explain the association of CETP with HDL-C. Indeed, three of the five novel variants (rs34065661, rs5817082, rs7499892) are independent of rs3764261., Conclusions: The causal variants in CETP that account for the association with HDL-C remain unknown. We used studies imputed to the 1000 Genomes reference panel for fine mapping of the CETP region. We identified and validated five variants within this region that may partly account for the association of the known variant (rs3764261), as well as other sources of genetic contribution to HDL-C., Competing Interests: PSM serves on the DSMB of a clinical trial of a device funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. SWvL is a former employee of Cavadis B.V. GP is a founder and stockholder of Cavadis B.V.

Published
2015
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